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Making `make install` work better by default. (#2004) # What does this PR do? Making `make install` a much better sane default to start local dev environments. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-06-04 11:38:46 -06:00
# This file is automatically @generated by Poetry 1.8.3 and should not be changed by hand.
feat(server): use latest flash attention commit (#543) @njhill FYI
2023-07-04 12:23:55 -06:00
[[package]]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
name = "accelerate"
Upgrading all versions. (#1759)
2024-04-18 09:17:40 -06:00
version = "0.29.3"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
description = "Accelerate"
chore: update to torch 2.1.0 (#1182) Close #1142
2023-11-23 05:38:50 -07:00
optional = true
feat: relax mistral requirements (#1351) Close #1253 Close #1279
2023-12-15 04:52:24 -07:00
python-versions = ">=3.8.0"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
files = [
Upgrading all versions. (#1759)
2024-04-18 09:17:40 -06:00
{file = "accelerate-0.29.3-py3-none-any.whl", hash = "sha256:99d633d4b6126817c5e554487406748be95c8d1d1e659dd2fd60657e35f532dd"},
{file = "accelerate-0.29.3.tar.gz", hash = "sha256:1a5a845b06b24b41736b219b2b20fd021ca5dff4070a252445fd6de736e347ac"},
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
]
feat(server): use latest flash attention commit (#543) @njhill FYI
2023-07-04 12:23:55 -06:00
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
[package.dependencies]
feat: relax mistral requirements (#1351) Close #1253 Close #1279
2023-12-15 04:52:24 -07:00
huggingface-hub = "*"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
numpy = ">=1.17"
packaging = ">=20.0"
psutil = "*"
pyyaml = "*"
feat: relax mistral requirements (#1351) Close #1253 Close #1279
2023-12-15 04:52:24 -07:00
safetensors = ">=0.3.1"
torch = ">=1.10.0"
feat(server): use latest flash attention commit (#543) @njhill FYI
2023-07-04 12:23:55 -06:00
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
[package.extras]
Update libraries (#1713) Co-authored-by: Nicolas Patry <patry.nicolas@protonmail.com>
2024-04-11 02:37:35 -06:00
dev = ["bitsandbytes", "black (>=23.1,<24.0)", "datasets", "deepspeed", "evaluate", "hf-doc-builder (>=0.3.0)", "parameterized", "pytest (>=7.2.0,<=8.0.0)", "pytest-subtests", "pytest-xdist", "rich", "ruff (>=0.2.1,<0.3.0)", "scikit-learn", "scipy", "timm", "torchpippy (>=0.2.0)", "tqdm", "transformers"]
feat: cohere (#1660)
2024-03-22 10:59:25 -06:00
quality = ["black (>=23.1,<24.0)", "hf-doc-builder (>=0.3.0)", "ruff (>=0.2.1,<0.3.0)"]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
rich = ["rich"]
sagemaker = ["sagemaker"]
Update libraries (#1713) Co-authored-by: Nicolas Patry <patry.nicolas@protonmail.com>
2024-04-11 02:37:35 -06:00
test-dev = ["bitsandbytes", "datasets", "deepspeed", "evaluate", "scikit-learn", "scipy", "timm", "torchpippy (>=0.2.0)", "tqdm", "transformers"]
feat: cohere (#1660)
2024-03-22 10:59:25 -06:00
test-prod = ["parameterized", "pytest (>=7.2.0,<=8.0.0)", "pytest-subtests", "pytest-xdist"]
feat: relax mistral requirements (#1351) Close #1253 Close #1279
2023-12-15 04:52:24 -07:00
test-trackers = ["comet-ml", "dvclive", "tensorboard", "wandb"]
Update libraries (#1713) Co-authored-by: Nicolas Patry <patry.nicolas@protonmail.com>
2024-04-11 02:37:35 -06:00
testing = ["bitsandbytes", "datasets", "deepspeed", "evaluate", "parameterized", "pytest (>=7.2.0,<=8.0.0)", "pytest-subtests", "pytest-xdist", "scikit-learn", "scipy", "timm", "torchpippy (>=0.2.0)", "tqdm", "transformers"]
feat(server): use latest flash attention commit (#543) @njhill FYI
2023-07-04 12:23:55 -06:00
Updating outlines to 0.0.46
2024-09-13 07:38:38 -06:00
[[package]]
name = "aiohappyeyeballs"
version = "2.4.0"
description = "Happy Eyeballs for asyncio"
optional = true
python-versions = ">=3.8"
files = [
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fix(server): fix missing datasets in quantize
2023-07-27 06:50:45 -06:00
[[package]]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
name = "aiohttp"
Updating outlines to 0.0.46
2024-09-13 07:38:38 -06:00
version = "3.10.5"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
description = "Async http client/server framework (asyncio)"
fix(server): fix missing datasets in quantize
2023-07-27 06:50:45 -06:00
optional = true
chore: update to torch 2.1.0 (#1182) Close #1142
2023-11-23 05:38:50 -07:00
python-versions = ">=3.8"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
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Updating outlines to 0.0.46
2024-09-13 07:38:38 -06:00
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fix(server): fix missing datasets in quantize
2023-07-27 06:50:45 -06:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
[package.dependencies]
Updating outlines to 0.0.46
2024-09-13 07:38:38 -06:00
aiohappyeyeballs = ">=2.3.0"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
aiosignal = ">=1.1.2"
chore: update to torch 2.1.0 (#1182) Close #1142
2023-11-23 05:38:50 -07:00
async-timeout = {version = ">=4.0,<5.0", markers = "python_version < \"3.11\""}
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
attrs = ">=17.3.0"
frozenlist = ">=1.1.1"
multidict = ">=4.5,<7.0"
yarl = ">=1.0,<2.0"
[package.extras]
Updating outlines to 0.0.46
2024-09-13 07:38:38 -06:00
speedups = ["Brotli", "aiodns (>=3.2.0)", "brotlicffi"]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
[[package]]
name = "aiosignal"
version = "1.3.1"
description = "aiosignal: a list of registered asynchronous callbacks"
optional = true
python-versions = ">=3.7"
files = [
fix(server): fix missing datasets in quantize
2023-07-27 06:50:45 -06:00
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{file = "aiosignal-1.3.1.tar.gz", hash = "sha256:54cd96e15e1649b75d6c87526a6ff0b6c1b0dd3459f43d9ca11d48c339b68cfc"},
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
[package.dependencies]
frozenlist = ">=1.1.0"
v1.4.1 (#1568)
2024-02-16 09:50:57 -07:00
[[package]]
name = "annotated-types"
Fix seeded output. (#1949) # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-24 07:36:13 -06:00
version = "0.7.0"
v1.4.1 (#1568)
2024-02-16 09:50:57 -07:00
description = "Reusable constraint types to use with typing.Annotated"
optional = true
python-versions = ">=3.8"
files = [
Fix seeded output. (#1949) # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-24 07:36:13 -06:00
{file = "annotated_types-0.7.0-py3-none-any.whl", hash = "sha256:1f02e8b43a8fbbc3f3e0d4f0f4bfc8131bcb4eebe8849b8e5c773f3a1c582a53"},
{file = "annotated_types-0.7.0.tar.gz", hash = "sha256:aff07c09a53a08bc8cfccb9c85b05f1aa9a2a6f23728d790723543408344ce89"},
v1.4.1 (#1568)
2024-02-16 09:50:57 -07:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
[[package]]
name = "async-timeout"
Adding Idefics multi modal model. (#842) Co-Authored-By: Victor Sanh <victorsanh@gmail.com> # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil --> --------- Co-authored-by: Victor Sanh <victorsanh@gmail.com>
2023-08-17 06:38:49 -06:00
version = "4.0.3"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
description = "Timeout context manager for asyncio programs"
optional = true
Adding Idefics multi modal model. (#842) Co-Authored-By: Victor Sanh <victorsanh@gmail.com> # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil --> --------- Co-authored-by: Victor Sanh <victorsanh@gmail.com>
2023-08-17 06:38:49 -06:00
python-versions = ">=3.7"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
files = [
Adding Idefics multi modal model. (#842) Co-Authored-By: Victor Sanh <victorsanh@gmail.com> # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil --> --------- Co-authored-by: Victor Sanh <victorsanh@gmail.com>
2023-08-17 06:38:49 -06:00
{file = "async-timeout-4.0.3.tar.gz", hash = "sha256:4640d96be84d82d02ed59ea2b7105a0f7b33abe8703703cd0ab0bf87c427522f"},
{file = "async_timeout-4.0.3-py3-none-any.whl", hash = "sha256:7405140ff1230c310e51dc27b3145b9092d659ce68ff733fb0cefe3ee42be028"},
fix(server): fix missing datasets in quantize
2023-07-27 06:50:45 -06:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
[[package]]
name = "attrs"
Updating outlines to 0.0.46
2024-09-13 07:38:38 -06:00
version = "24.2.0"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
description = "Classes Without Boilerplate"
optional = true
python-versions = ">=3.7"
files = [
Updating outlines to 0.0.46
2024-09-13 07:38:38 -06:00
{file = "attrs-24.2.0-py3-none-any.whl", hash = "sha256:81921eb96de3191c8258c199618104dd27ac608d9366f5e35d011eae1867ede2"},
{file = "attrs-24.2.0.tar.gz", hash = "sha256:5cfb1b9148b5b086569baec03f20d7b6bf3bcacc9a42bebf87ffaaca362f6346"},
fix(server): fix missing datasets in quantize
2023-07-27 06:50:45 -06:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
[package.extras]
Updating outlines to 0.0.46
2024-09-13 07:38:38 -06:00
benchmark = ["cloudpickle", "hypothesis", "mypy (>=1.11.1)", "pympler", "pytest (>=4.3.0)", "pytest-codspeed", "pytest-mypy-plugins", "pytest-xdist[psutil]"]
cov = ["cloudpickle", "coverage[toml] (>=5.3)", "hypothesis", "mypy (>=1.11.1)", "pympler", "pytest (>=4.3.0)", "pytest-mypy-plugins", "pytest-xdist[psutil]"]
dev = ["cloudpickle", "hypothesis", "mypy (>=1.11.1)", "pre-commit", "pympler", "pytest (>=4.3.0)", "pytest-mypy-plugins", "pytest-xdist[psutil]"]
docs = ["cogapp", "furo", "myst-parser", "sphinx", "sphinx-notfound-page", "sphinxcontrib-towncrier", "towncrier (<24.7)"]
tests = ["cloudpickle", "hypothesis", "mypy (>=1.11.1)", "pympler", "pytest (>=4.3.0)", "pytest-mypy-plugins", "pytest-xdist[psutil]"]
tests-mypy = ["mypy (>=1.11.1)", "pytest-mypy-plugins"]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
[[package]]
name = "bitsandbytes"
Updating outlines to 0.0.46
2024-09-13 07:38:38 -06:00
version = "0.43.3"
Merge BNB 4bit. (#770) # What does this PR do? See #626 <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil --> --------- Co-authored-by: krzim <zimmerk4@live.com>
2023-08-03 15:00:59 -06:00
description = "k-bit optimizers and matrix multiplication routines."
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
optional = true
python-versions = "*"
files = [
Updating outlines to 0.0.46
2024-09-13 07:38:38 -06:00
{file = "bitsandbytes-0.43.3-py3-none-manylinux_2_24_x86_64.whl", hash = "sha256:cc99507c352be0715098b2c7577b690dd158972dc4ea10c7495bac104c7c79f0"},
{file = "bitsandbytes-0.43.3-py3-none-win_amd64.whl", hash = "sha256:257f6552f2144748a84e6c44e1f7a98f3da888f675ed74e18fd7f7eb13c6cafa"},
feat(server): use latest flash attention commit (#543) @njhill FYI
2023-07-04 12:23:55 -06:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
feat: cohere (#1660)
2024-03-22 10:59:25 -06:00
[package.dependencies]
numpy = "*"
torch = "*"
[package.extras]
benchmark = ["matplotlib", "pandas"]
test = ["scipy"]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
[[package]]
name = "certifi"
Updating outlines to 0.0.46
2024-09-13 07:38:38 -06:00
version = "2024.8.30"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
description = "Python package for providing Mozilla's CA Bundle."
optional = false
python-versions = ">=3.6"
files = [
Updating outlines to 0.0.46
2024-09-13 07:38:38 -06:00
{file = "certifi-2024.8.30-py3-none-any.whl", hash = "sha256:922820b53db7a7257ffbda3f597266d435245903d80737e34f8a45ff3e3230d8"},
{file = "certifi-2024.8.30.tar.gz", hash = "sha256:bec941d2aa8195e248a60b31ff9f0558284cf01a52591ceda73ea9afffd69fd9"},
feat(server): use latest flash attention commit (#543) @njhill FYI
2023-07-04 12:23:55 -06:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
[[package]]
name = "charset-normalizer"
chore: update to torch 2.1.0 (#1182) Close #1142
2023-11-23 05:38:50 -07:00
version = "3.3.2"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
description = "The Real First Universal Charset Detector. Open, modern and actively maintained alternative to Chardet."
optional = false
python-versions = ">=3.7.0"
files = [
chore: update to torch 2.1.0 (#1182) Close #1142
2023-11-23 05:38:50 -07:00
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feat(server): use latest flash attention commit (#543) @njhill FYI
2023-07-04 12:23:55 -06:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
[[package]]
name = "click"
New release. (#941) # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-29 06:28:22 -06:00
version = "8.1.7"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
description = "Composable command line interface toolkit"
optional = false
python-versions = ">=3.7"
files = [
New release. (#941) # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-29 06:28:22 -06:00
{file = "click-8.1.7-py3-none-any.whl", hash = "sha256:ae74fb96c20a0277a1d615f1e4d73c8414f5a98db8b799a7931d1582f3390c28"},
{file = "click-8.1.7.tar.gz", hash = "sha256:ca9853ad459e787e2192211578cc907e7594e294c7ccc834310722b41b9ca6de"},
feat(server): use latest flash attention commit (#543) @njhill FYI
2023-07-04 12:23:55 -06:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
[package.dependencies]
colorama = {version = "*", markers = "platform_system == \"Windows\""}
v1.4.1 (#1568)
2024-02-16 09:50:57 -07:00
[[package]]
name = "cloudpickle"
version = "3.0.0"
description = "Pickler class to extend the standard pickle.Pickler functionality"
optional = true
python-versions = ">=3.8"
files = [
{file = "cloudpickle-3.0.0-py3-none-any.whl", hash = "sha256:246ee7d0c295602a036e86369c77fecda4ab17b506496730f2f576d9016fd9c7"},
{file = "cloudpickle-3.0.0.tar.gz", hash = "sha256:996d9a482c6fb4f33c1a35335cf8afd065d2a56e973270364840712d9131a882"},
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
[[package]]
name = "colorama"
version = "0.4.6"
description = "Cross-platform colored terminal text."
optional = false
python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,!=3.6.*,>=2.7"
files = [
feat(server): use latest flash attention commit (#543) @njhill FYI
2023-07-04 12:23:55 -06:00
{file = "colorama-0.4.6-py2.py3-none-any.whl", hash = "sha256:4f1d9991f5acc0ca119f9d443620b77f9d6b33703e51011c16baf57afb285fc6"},
{file = "colorama-0.4.6.tar.gz", hash = "sha256:08695f5cb7ed6e0531a20572697297273c47b8cae5a63ffc6d6ed5c201be6e44"},
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
[[package]]
name = "datasets"
Updating outlines to 0.0.46
2024-09-13 07:38:38 -06:00
version = "2.21.0"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
description = "HuggingFace community-driven open-source library of datasets"
optional = true
python-versions = ">=3.8.0"
files = [
Updating outlines to 0.0.46
2024-09-13 07:38:38 -06:00
{file = "datasets-2.21.0-py3-none-any.whl", hash = "sha256:25e4e097110ce28824b746a107727ada94024cba11db8bc588d468414692b65a"},
{file = "datasets-2.21.0.tar.gz", hash = "sha256:998f85a8460f1bd982e5bd058f8a0808eef424249e3df1e8cdd594ccd0dc8ba2"},
fix(server): fix missing datasets in quantize
2023-07-27 06:50:45 -06:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
[package.dependencies]
aiohttp = "*"
Softcapping for gemma2. (#2273) * Softcapping for gemma2. * Less clutter. * No access to transformers config, only config_dict here. * 0.0 is the null value in the C++ API.
2024-07-22 10:27:10 -06:00
dill = ">=0.3.0,<0.3.9"
filelock = "*"
Updating outlines to 0.0.46
2024-09-13 07:38:38 -06:00
fsspec = {version = ">=2023.1.0,<=2024.6.1", extras = ["http"]}
Softcapping for gemma2. (#2273) * Softcapping for gemma2. * Less clutter. * No access to transformers config, only config_dict here. * 0.0 is the null value in the C++ API.
2024-07-22 10:27:10 -06:00
huggingface-hub = ">=0.21.2"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
multiprocess = "*"
numpy = ">=1.17"
packaging = "*"
pandas = "*"
Softcapping for gemma2. (#2273) * Softcapping for gemma2. * Less clutter. * No access to transformers config, only config_dict here. * 0.0 is the null value in the C++ API.
2024-07-22 10:27:10 -06:00
pyarrow = ">=15.0.0"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
pyyaml = ">=5.1"
Softcapping for gemma2. (#2273) * Softcapping for gemma2. * Less clutter. * No access to transformers config, only config_dict here. * 0.0 is the null value in the C++ API.
2024-07-22 10:27:10 -06:00
requests = ">=2.32.2"
tqdm = ">=4.66.3"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
xxhash = "*"
[package.extras]
Softcapping for gemma2. (#2273) * Softcapping for gemma2. * Less clutter. * No access to transformers config, only config_dict here. * 0.0 is the null value in the C++ API.
2024-07-22 10:27:10 -06:00
apache-beam = ["apache-beam (>=2.26.0)"]
Updating outlines to 0.0.46
2024-09-13 07:38:38 -06:00
audio = ["librosa", "soundfile (>=0.12.1)", "soxr (>=0.4.0)"]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
benchmarks = ["tensorflow (==2.12.0)", "torch (==2.0.1)", "transformers (==4.30.1)"]
Updating outlines to 0.0.46
2024-09-13 07:38:38 -06:00
dev = ["Pillow (>=9.4.0)", "absl-py", "decorator", "elasticsearch (<8.0.0)", "faiss-cpu (>=1.8.0.post1)", "jax (>=0.3.14)", "jaxlib (>=0.3.14)", "joblib (<1.3.0)", "joblibspark", "librosa", "lz4", "moto[server]", "polars[timezone] (>=0.20.0)", "protobuf (<4.0.0)", "py7zr", "pyspark (>=3.4)", "pytest", "pytest-datadir", "pytest-xdist", "rarfile (>=4.0)", "ruff (>=0.3.0)", "s3fs", "s3fs (>=2021.11.1)", "soundfile (>=0.12.1)", "soxr (>=0.4.0)", "sqlalchemy", "tensorflow (>=2.16.0)", "tensorflow (>=2.6.0)", "tensorflow (>=2.6.0)", "tiktoken", "torch", "torch (>=2.0.0)", "transformers", "transformers (>=4.42.0)", "typing-extensions (>=4.6.1)", "zstandard"]
Softcapping for gemma2. (#2273) * Softcapping for gemma2. * Less clutter. * No access to transformers config, only config_dict here. * 0.0 is the null value in the C++ API.
2024-07-22 10:27:10 -06:00
docs = ["s3fs", "tensorflow (>=2.6.0)", "torch", "transformers"]
jax = ["jax (>=0.3.14)", "jaxlib (>=0.3.14)"]
Updating outlines to 0.0.46
2024-09-13 07:38:38 -06:00
metrics-tests = ["Werkzeug (>=1.0.1)", "accelerate", "bert-score (>=0.3.6)", "jiwer", "langdetect", "mauve-text", "nltk (<3.8.2)", "requests-file (>=1.5.1)", "rouge-score", "sacrebleu", "sacremoses", "scikit-learn", "scipy", "sentencepiece", "seqeval", "six (>=1.15.0,<1.16.0)", "spacy (>=3.0.0)", "texttable (>=1.6.3)", "tldextract", "tldextract (>=3.1.0)", "toml (>=0.10.1)", "typer (<0.5.0)"]
Softcapping for gemma2. (#2273) * Softcapping for gemma2. * Less clutter. * No access to transformers config, only config_dict here. * 0.0 is the null value in the C++ API.
2024-07-22 10:27:10 -06:00
quality = ["ruff (>=0.3.0)"]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
s3 = ["s3fs"]
Softcapping for gemma2. (#2273) * Softcapping for gemma2. * Less clutter. * No access to transformers config, only config_dict here. * 0.0 is the null value in the C++ API.
2024-07-22 10:27:10 -06:00
tensorflow = ["tensorflow (>=2.6.0)"]
tensorflow-gpu = ["tensorflow (>=2.6.0)"]
Updating outlines to 0.0.46
2024-09-13 07:38:38 -06:00
tests = ["Pillow (>=9.4.0)", "absl-py", "decorator", "elasticsearch (<8.0.0)", "faiss-cpu (>=1.8.0.post1)", "jax (>=0.3.14)", "jaxlib (>=0.3.14)", "joblib (<1.3.0)", "joblibspark", "librosa", "lz4", "moto[server]", "polars[timezone] (>=0.20.0)", "protobuf (<4.0.0)", "py7zr", "pyspark (>=3.4)", "pytest", "pytest-datadir", "pytest-xdist", "rarfile (>=4.0)", "s3fs (>=2021.11.1)", "soundfile (>=0.12.1)", "soxr (>=0.4.0)", "sqlalchemy", "tensorflow (>=2.16.0)", "tensorflow (>=2.6.0)", "tiktoken", "torch (>=2.0.0)", "transformers (>=4.42.0)", "typing-extensions (>=4.6.1)", "zstandard"]
tests-numpy2 = ["Pillow (>=9.4.0)", "absl-py", "decorator", "elasticsearch (<8.0.0)", "jax (>=0.3.14)", "jaxlib (>=0.3.14)", "joblib (<1.3.0)", "joblibspark", "librosa", "lz4", "moto[server]", "polars[timezone] (>=0.20.0)", "protobuf (<4.0.0)", "py7zr", "pyspark (>=3.4)", "pytest", "pytest-datadir", "pytest-xdist", "rarfile (>=4.0)", "s3fs (>=2021.11.1)", "soundfile (>=0.12.1)", "soxr (>=0.4.0)", "sqlalchemy", "tiktoken", "torch (>=2.0.0)", "typing-extensions (>=4.6.1)", "zstandard"]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
torch = ["torch"]
Softcapping for gemma2. (#2273) * Softcapping for gemma2. * Less clutter. * No access to transformers config, only config_dict here. * 0.0 is the null value in the C++ API.
2024-07-22 10:27:10 -06:00
vision = ["Pillow (>=9.4.0)"]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
[[package]]
This should prevent the PyTorch overriding. (#767) # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 13:54:39 -06:00
name = "deprecated"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
version = "1.2.14"
description = "Python @deprecated decorator to deprecate old python classes, functions or methods."
optional = false
python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
files = [
feat(server): use latest flash attention commit (#543) @njhill FYI
2023-07-04 12:23:55 -06:00
{file = "Deprecated-1.2.14-py2.py3-none-any.whl", hash = "sha256:6fac8b097794a90302bdbb17b9b815e732d3c4720583ff1b198499d78470466c"},
{file = "Deprecated-1.2.14.tar.gz", hash = "sha256:e5323eb936458dccc2582dc6f9c322c852a775a27065ff2b0c4970b9d53d01b3"},
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
[package.dependencies]
wrapt = ">=1.10,<2"
[package.extras]
dev = ["PyTest", "PyTest-Cov", "bump2version (<1)", "sphinx (<2)", "tox"]
[[package]]
name = "dill"
Softcapping for gemma2. (#2273) * Softcapping for gemma2. * Less clutter. * No access to transformers config, only config_dict here. * 0.0 is the null value in the C++ API.
2024-07-22 10:27:10 -06:00
version = "0.3.8"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
description = "serialize all of Python"
optional = true
Softcapping for gemma2. (#2273) * Softcapping for gemma2. * Less clutter. * No access to transformers config, only config_dict here. * 0.0 is the null value in the C++ API.
2024-07-22 10:27:10 -06:00
python-versions = ">=3.8"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
files = [
Softcapping for gemma2. (#2273) * Softcapping for gemma2. * Less clutter. * No access to transformers config, only config_dict here. * 0.0 is the null value in the C++ API.
2024-07-22 10:27:10 -06:00
{file = "dill-0.3.8-py3-none-any.whl", hash = "sha256:c36ca9ffb54365bdd2f8eb3eff7d2a21237f8452b57ace88b1ac615b7e815bd7"},
{file = "dill-0.3.8.tar.gz", hash = "sha256:3ebe3c479ad625c4553aca177444d89b486b1d84982eeacded644afc0cf797ca"},
fix(server): fix missing datasets in quantize
2023-07-27 06:50:45 -06:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
[package.extras]
graph = ["objgraph (>=1.7.2)"]
Softcapping for gemma2. (#2273) * Softcapping for gemma2. * Less clutter. * No access to transformers config, only config_dict here. * 0.0 is the null value in the C++ API.
2024-07-22 10:27:10 -06:00
profile = ["gprof2dot (>=2022.7.29)"]
v1.4.1 (#1568)
2024-02-16 09:50:57 -07:00
[[package]]
name = "diskcache"
version = "5.6.3"
description = "Disk Cache -- Disk and file backed persistent cache."
optional = true
python-versions = ">=3"
files = [
{file = "diskcache-5.6.3-py3-none-any.whl", hash = "sha256:5e31b2d5fbad117cc363ebaf6b689474db18a1f6438bc82358b024abd4c2ca19"},
{file = "diskcache-5.6.3.tar.gz", hash = "sha256:2c3a3fa2743d8535d832ec61c2054a1641f41775aa7c556758a109941e33e4fc"},
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
[[package]]
name = "einops"
version = "0.6.1"
description = "A new flavour of deep learning operations"
optional = false
python-versions = ">=3.7"
files = [
feat(server): use latest flash attention commit (#543) @njhill FYI
2023-07-04 12:23:55 -06:00
{file = "einops-0.6.1-py3-none-any.whl", hash = "sha256:99149e46cc808956b174932fe563d920db4d6e5dadb8c6ecdaa7483b7ef7cfc3"},
{file = "einops-0.6.1.tar.gz", hash = "sha256:f95f8d00f4ded90dbc4b19b6f98b177332614b0357dde66997f3ae5d474dc8c8"},
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
[[package]]
name = "exceptiongroup"
Softcapping for gemma2. (#2273) * Softcapping for gemma2. * Less clutter. * No access to transformers config, only config_dict here. * 0.0 is the null value in the C++ API.
2024-07-22 10:27:10 -06:00
version = "1.2.2"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
description = "Backport of PEP 654 (exception groups)"
optional = false
python-versions = ">=3.7"
files = [
Softcapping for gemma2. (#2273) * Softcapping for gemma2. * Less clutter. * No access to transformers config, only config_dict here. * 0.0 is the null value in the C++ API.
2024-07-22 10:27:10 -06:00
{file = "exceptiongroup-1.2.2-py3-none-any.whl", hash = "sha256:3111b9d131c238bec2f8f516e123e14ba243563fb135d3fe885990585aa7795b"},
{file = "exceptiongroup-1.2.2.tar.gz", hash = "sha256:47c2edf7c6738fafb49fd34290706d1a1a2f4d1c6df275526b62cbb4aa5393cc"},
feat(server): use latest flash attention commit (#543) @njhill FYI
2023-07-04 12:23:55 -06:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
[package.extras]
test = ["pytest (>=6)"]
[[package]]
name = "filelock"
Updating outlines to 0.0.46
2024-09-13 07:38:38 -06:00
version = "3.16.0"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
description = "A platform independent file lock."
optional = false
New release. (#941) # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-29 06:28:22 -06:00
python-versions = ">=3.8"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
files = [
Updating outlines to 0.0.46
2024-09-13 07:38:38 -06:00
{file = "filelock-3.16.0-py3-none-any.whl", hash = "sha256:f6ed4c963184f4c84dd5557ce8fece759a3724b37b80c6c4f20a2f63a4dc6609"},
{file = "filelock-3.16.0.tar.gz", hash = "sha256:81de9eb8453c769b63369f87f11131a7ab04e367f8d97ad39dc230daa07e3bec"},
feat(server): use latest flash attention commit (#543) @njhill FYI
2023-07-04 12:23:55 -06:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
[package.extras]
Updating outlines to 0.0.46
2024-09-13 07:38:38 -06:00
docs = ["furo (>=2024.8.6)", "sphinx (>=8.0.2)", "sphinx-autodoc-typehints (>=2.4)"]
testing = ["covdefaults (>=2.3)", "coverage (>=7.6.1)", "diff-cover (>=9.1.1)", "pytest (>=8.3.2)", "pytest-asyncio (>=0.24)", "pytest-cov (>=5)", "pytest-mock (>=3.14)", "pytest-timeout (>=2.3.1)", "virtualenv (>=20.26.3)"]
typing = ["typing-extensions (>=4.12.2)"]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
[[package]]
name = "frozenlist"
feat: relax mistral requirements (#1351) Close #1253 Close #1279
2023-12-15 04:52:24 -07:00
version = "1.4.1"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
description = "A list-like structure which implements collections.abc.MutableSequence"
optional = true
python-versions = ">=3.8"
files = [
feat: relax mistral requirements (#1351) Close #1253 Close #1279
2023-12-15 04:52:24 -07:00
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fix(server): fix missing datasets in quantize
2023-07-27 06:50:45 -06:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
[[package]]
name = "fsspec"
Updating outlines to 0.0.46
2024-09-13 07:38:38 -06:00
version = "2024.6.1"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
description = "File-system specification"
optional = false
python-versions = ">=3.8"
files = [
Updating outlines to 0.0.46
2024-09-13 07:38:38 -06:00
{file = "fsspec-2024.6.1-py3-none-any.whl", hash = "sha256:3cb443f8bcd2efb31295a5b9fdb02aee81d8452c80d28f97a6d0959e6cee101e"},
{file = "fsspec-2024.6.1.tar.gz", hash = "sha256:fad7d7e209dd4c1208e3bbfda706620e0da5142bebbd9c384afb95b07e798e49"},
feat(server): use latest flash attention commit (#543) @njhill FYI
2023-07-04 12:23:55 -06:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
[package.dependencies]
aiohttp = {version = "<4.0.0a0 || >4.0.0a0,<4.0.0a1 || >4.0.0a1", optional = true, markers = "extra == \"http\""}
[package.extras]
abfs = ["adlfs"]
adl = ["adlfs"]
arrow = ["pyarrow (>=1)"]
dask = ["dask", "distributed"]
Fix seeded output. (#1949) # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-24 07:36:13 -06:00
dev = ["pre-commit", "ruff"]
Updating outlines to 0.0.46
2024-09-13 07:38:38 -06:00
doc = ["numpydoc", "sphinx", "sphinx-design", "sphinx-rtd-theme", "yarl"]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
dropbox = ["dropbox", "dropboxdrivefs", "requests"]
full = ["adlfs", "aiohttp (!=4.0.0a0,!=4.0.0a1)", "dask", "distributed", "dropbox", "dropboxdrivefs", "fusepy", "gcsfs", "libarchive-c", "ocifs", "panel", "paramiko", "pyarrow (>=1)", "pygit2", "requests", "s3fs", "smbprotocol", "tqdm"]
fuse = ["fusepy"]
gcs = ["gcsfs"]
git = ["pygit2"]
github = ["requests"]
gs = ["gcsfs"]
gui = ["panel"]
hdfs = ["pyarrow (>=1)"]
feat: cohere (#1660)
2024-03-22 10:59:25 -06:00
http = ["aiohttp (!=4.0.0a0,!=4.0.0a1)"]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
libarchive = ["libarchive-c"]
oci = ["ocifs"]
s3 = ["s3fs"]
sftp = ["paramiko"]
smb = ["smbprotocol"]
ssh = ["paramiko"]
Fix seeded output. (#1949) # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-24 07:36:13 -06:00
test = ["aiohttp (!=4.0.0a0,!=4.0.0a1)", "numpy", "pytest", "pytest-asyncio (!=0.22.0)", "pytest-benchmark", "pytest-cov", "pytest-mock", "pytest-recording", "pytest-rerunfailures", "requests"]
test-downstream = ["aiobotocore (>=2.5.4,<3.0.0)", "dask-expr", "dask[dataframe,test]", "moto[server] (>4,<5)", "pytest-timeout", "xarray"]
test-full = ["adlfs", "aiohttp (!=4.0.0a0,!=4.0.0a1)", "cloudpickle", "dask", "distributed", "dropbox", "dropboxdrivefs", "fastparquet", "fusepy", "gcsfs", "jinja2", "kerchunk", "libarchive-c", "lz4", "notebook", "numpy", "ocifs", "pandas", "panel", "paramiko", "pyarrow", "pyarrow (>=1)", "pyftpdlib", "pygit2", "pytest", "pytest-asyncio (!=0.22.0)", "pytest-benchmark", "pytest-cov", "pytest-mock", "pytest-recording", "pytest-rerunfailures", "python-snappy", "requests", "smbprotocol", "tqdm", "urllib3", "zarr", "zstandard"]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
tqdm = ["tqdm"]
[[package]]
name = "googleapis-common-protos"
Updating outlines to 0.0.46
2024-09-13 07:38:38 -06:00
version = "1.65.0"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
description = "Common protobufs used in Google APIs"
optional = false
python-versions = ">=3.7"
files = [
Updating outlines to 0.0.46
2024-09-13 07:38:38 -06:00
{file = "googleapis_common_protos-1.65.0-py2.py3-none-any.whl", hash = "sha256:2972e6c496f435b92590fd54045060867f3fe9be2c82ab148fc8885035479a63"},
{file = "googleapis_common_protos-1.65.0.tar.gz", hash = "sha256:334a29d07cddc3aa01dee4988f9afd9b2916ee2ff49d6b757155dc0d197852c0"},
feat(server): use latest flash attention commit (#543) @njhill FYI
2023-07-04 12:23:55 -06:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
[package.dependencies]
Softcapping for gemma2. (#2273) * Softcapping for gemma2. * Less clutter. * No access to transformers config, only config_dict here. * 0.0 is the null value in the C++ API.
2024-07-22 10:27:10 -06:00
protobuf = ">=3.20.2,<4.21.1 || >4.21.1,<4.21.2 || >4.21.2,<4.21.3 || >4.21.3,<4.21.4 || >4.21.4,<4.21.5 || >4.21.5,<6.0.0.dev0"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
[package.extras]
grpc = ["grpcio (>=1.44.0,<2.0.0.dev0)"]
[[package]]
name = "grpc-interceptor"
chore: update to torch 2.1.0 (#1182) Close #1142
2023-11-23 05:38:50 -07:00
version = "0.15.4"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
description = "Simplifies gRPC interceptors"
optional = false
python-versions = ">=3.7,<4.0"
files = [
chore: update to torch 2.1.0 (#1182) Close #1142
2023-11-23 05:38:50 -07:00
{file = "grpc-interceptor-0.15.4.tar.gz", hash = "sha256:1f45c0bcb58b6f332f37c637632247c9b02bc6af0fdceb7ba7ce8d2ebbfb0926"},
{file = "grpc_interceptor-0.15.4-py3-none-any.whl", hash = "sha256:0035f33228693ed3767ee49d937bac424318db173fef4d2d0170b3215f254d9d"},
feat(server): use latest flash attention commit (#543) @njhill FYI
2023-07-04 12:23:55 -06:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
[package.dependencies]
grpcio = ">=1.49.1,<2.0.0"
[package.extras]
testing = ["protobuf (>=4.21.9)"]
[[package]]
name = "grpcio"
Updating outlines to 0.0.46
2024-09-13 07:38:38 -06:00
version = "1.66.1"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
description = "HTTP/2-based RPC framework"
optional = false
Granite support? (#1882) # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-13 05:46:29 -06:00
python-versions = ">=3.8"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
files = [
Updating outlines to 0.0.46
2024-09-13 07:38:38 -06:00
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feat(server): use latest flash attention commit (#543) @njhill FYI
2023-07-04 12:23:55 -06:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
[package.extras]
Updating outlines to 0.0.46
2024-09-13 07:38:38 -06:00
protobuf = ["grpcio-tools (>=1.66.1)"]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
[[package]]
name = "grpcio-reflection"
Updating outlines to 0.0.46
2024-09-13 07:38:38 -06:00
version = "1.62.3"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
description = "Standard Protobuf Reflection Service for gRPC"
optional = false
python-versions = ">=3.6"
files = [
Updating outlines to 0.0.46
2024-09-13 07:38:38 -06:00
{file = "grpcio-reflection-1.62.3.tar.gz", hash = "sha256:cb84682933c400bddf94dd94f928d1c6570f500b6dd255973d4bfb495b82585f"},
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feat(server): use latest flash attention commit (#543) @njhill FYI
2023-07-04 12:23:55 -06:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
[package.dependencies]
Updating outlines to 0.0.46
2024-09-13 07:38:38 -06:00
grpcio = ">=1.62.3"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
protobuf = ">=4.21.6"
[[package]]
name = "grpcio-status"
Updating outlines to 0.0.46
2024-09-13 07:38:38 -06:00
version = "1.62.3"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
description = "Status proto mapping for gRPC"
optional = false
python-versions = ">=3.6"
files = [
Updating outlines to 0.0.46
2024-09-13 07:38:38 -06:00
{file = "grpcio-status-1.62.3.tar.gz", hash = "sha256:289bdd7b2459794a12cf95dc0cb727bd4a1742c37bd823f760236c937e53a485"},
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feat(server): use latest flash attention commit (#543) @njhill FYI
2023-07-04 12:23:55 -06:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
[package.dependencies]
googleapis-common-protos = ">=1.5.5"
Updating outlines to 0.0.46
2024-09-13 07:38:38 -06:00
grpcio = ">=1.62.3"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
protobuf = ">=4.21.6"
[[package]]
name = "grpcio-tools"
Updating outlines to 0.0.46
2024-09-13 07:38:38 -06:00
version = "1.62.3"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
description = "Protobuf code generator for gRPC"
optional = false
python-versions = ">=3.7"
files = [
Updating outlines to 0.0.46
2024-09-13 07:38:38 -06:00
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feat(server): use latest flash attention commit (#543) @njhill FYI
2023-07-04 12:23:55 -06:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
[package.dependencies]
Updating outlines to 0.0.46
2024-09-13 07:38:38 -06:00
grpcio = ">=1.62.3"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
protobuf = ">=4.21.6,<5.0dev"
setuptools = "*"
[[package]]
name = "hf-transfer"
Add support for Llama 3 rotary embeddings (#2286) * Add support for Llama 3 rotary embeddings * Update transformers to 4.43
2024-07-23 09:18:54 -06:00
version = "0.1.8"
description = "Speed up file transfers with the Hugging Face Hub."
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
optional = false
python-versions = ">=3.7"
files = [
Add support for Llama 3 rotary embeddings (#2286) * Add support for Llama 3 rotary embeddings * Update transformers to 4.43
2024-07-23 09:18:54 -06:00
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feat(server): use latest flash attention commit (#543) @njhill FYI
2023-07-04 12:23:55 -06:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
[[package]]
name = "huggingface-hub"
Softcapping for gemma2. (#2273) * Softcapping for gemma2. * Less clutter. * No access to transformers config, only config_dict here. * 0.0 is the null value in the C++ API.
2024-07-22 10:27:10 -06:00
version = "0.23.5"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
description = "Client library to download and publish models, datasets and other repos on the huggingface.co hub"
optional = false
feat: relax mistral requirements (#1351) Close #1253 Close #1279
2023-12-15 04:52:24 -07:00
python-versions = ">=3.8.0"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
files = [
Softcapping for gemma2. (#2273) * Softcapping for gemma2. * Less clutter. * No access to transformers config, only config_dict here. * 0.0 is the null value in the C++ API.
2024-07-22 10:27:10 -06:00
{file = "huggingface_hub-0.23.5-py3-none-any.whl", hash = "sha256:d7a7d337615e11a45cc14a0ce5a605db6b038dc24af42866f731684825226e90"},
{file = "huggingface_hub-0.23.5.tar.gz", hash = "sha256:67a9caba79b71235be3752852ca27da86bd54311d2424ca8afdb8dda056edf98"},
feat(server): use latest flash attention commit (#543) @njhill FYI
2023-07-04 12:23:55 -06:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
[package.dependencies]
filelock = "*"
feat: relax mistral requirements (#1351) Close #1253 Close #1279
2023-12-15 04:52:24 -07:00
fsspec = ">=2023.5.0"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
packaging = ">=20.9"
pyyaml = ">=5.1"
requests = "*"
tqdm = ">=4.42.1"
typing-extensions = ">=3.7.4.3"
[package.extras]
Pali gemma modeling (#1895) This PR adds paligemma modeling code Blog post: https://huggingface.co/blog/paligemma Transformers PR: https://github.com/huggingface/transformers/pull/30814 install the latest changes and run with ```bash # get the weights # text-generation-server download-weights gv-hf/PaliGemma-base-224px-hf # run TGI text-generation-launcher --model-id gv-hf/PaliGemma-base-224px-hf ``` basic example sending various requests ```python from huggingface_hub import InferenceClient client = InferenceClient("http://127.0.0.1:3000") images = [ "https://huggingface.co/datasets/hf-internal-testing/fixtures-captioning/resolve/main/cow_beach_1.png", "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/transformers/rabbit.png", ] prompts = [ "What animal is in this image?", "Name three colors in this image.", "What are 10 colors in this image?", "Where is the cow standing?", "answer en Where is the cow standing?", "Is there a bird in the image?", "Is ther a cow in the image?", "Is there a rabbit in the image?", "how many birds are in the image?", "how many rabbits are in the image?", ] for img in images: print(f"\nImage: {img.split('/')[-1]}") for prompt in prompts: inputs = f"![]({img}){prompt}\n" json_data = { "inputs": inputs, "parameters": { "max_new_tokens": 30, "do_sample": False, }, } generated_output = client.text_generation(prompt, max_new_tokens=30, stream=False) print([f"{prompt}\n{generated_output}"]) ``` --------- Co-authored-by: Nicolas Patry <patry.nicolas@protonmail.com>
2024-05-15 22:58:47 -06:00
all = ["InquirerPy (==0.3.4)", "Jinja2", "Pillow", "aiohttp", "fastapi", "gradio", "jedi", "minijinja (>=1.0)", "mypy (==1.5.1)", "numpy", "pytest", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-rerunfailures", "pytest-vcr", "pytest-xdist", "ruff (>=0.3.0)", "soundfile", "types-PyYAML", "types-requests", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)", "urllib3 (<2.0)"]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
cli = ["InquirerPy (==0.3.4)"]
Pali gemma modeling (#1895) This PR adds paligemma modeling code Blog post: https://huggingface.co/blog/paligemma Transformers PR: https://github.com/huggingface/transformers/pull/30814 install the latest changes and run with ```bash # get the weights # text-generation-server download-weights gv-hf/PaliGemma-base-224px-hf # run TGI text-generation-launcher --model-id gv-hf/PaliGemma-base-224px-hf ``` basic example sending various requests ```python from huggingface_hub import InferenceClient client = InferenceClient("http://127.0.0.1:3000") images = [ "https://huggingface.co/datasets/hf-internal-testing/fixtures-captioning/resolve/main/cow_beach_1.png", "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/transformers/rabbit.png", ] prompts = [ "What animal is in this image?", "Name three colors in this image.", "What are 10 colors in this image?", "Where is the cow standing?", "answer en Where is the cow standing?", "Is there a bird in the image?", "Is ther a cow in the image?", "Is there a rabbit in the image?", "how many birds are in the image?", "how many rabbits are in the image?", ] for img in images: print(f"\nImage: {img.split('/')[-1]}") for prompt in prompts: inputs = f"![]({img}){prompt}\n" json_data = { "inputs": inputs, "parameters": { "max_new_tokens": 30, "do_sample": False, }, } generated_output = client.text_generation(prompt, max_new_tokens=30, stream=False) print([f"{prompt}\n{generated_output}"]) ``` --------- Co-authored-by: Nicolas Patry <patry.nicolas@protonmail.com>
2024-05-15 22:58:47 -06:00
dev = ["InquirerPy (==0.3.4)", "Jinja2", "Pillow", "aiohttp", "fastapi", "gradio", "jedi", "minijinja (>=1.0)", "mypy (==1.5.1)", "numpy", "pytest", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-rerunfailures", "pytest-vcr", "pytest-xdist", "ruff (>=0.3.0)", "soundfile", "types-PyYAML", "types-requests", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)", "urllib3 (<2.0)"]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
fastai = ["fastai (>=2.4)", "fastcore (>=1.3.27)", "toml"]
Pali gemma modeling (#1895) This PR adds paligemma modeling code Blog post: https://huggingface.co/blog/paligemma Transformers PR: https://github.com/huggingface/transformers/pull/30814 install the latest changes and run with ```bash # get the weights # text-generation-server download-weights gv-hf/PaliGemma-base-224px-hf # run TGI text-generation-launcher --model-id gv-hf/PaliGemma-base-224px-hf ``` basic example sending various requests ```python from huggingface_hub import InferenceClient client = InferenceClient("http://127.0.0.1:3000") images = [ "https://huggingface.co/datasets/hf-internal-testing/fixtures-captioning/resolve/main/cow_beach_1.png", "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/transformers/rabbit.png", ] prompts = [ "What animal is in this image?", "Name three colors in this image.", "What are 10 colors in this image?", "Where is the cow standing?", "answer en Where is the cow standing?", "Is there a bird in the image?", "Is ther a cow in the image?", "Is there a rabbit in the image?", "how many birds are in the image?", "how many rabbits are in the image?", ] for img in images: print(f"\nImage: {img.split('/')[-1]}") for prompt in prompts: inputs = f"![]({img}){prompt}\n" json_data = { "inputs": inputs, "parameters": { "max_new_tokens": 30, "do_sample": False, }, } generated_output = client.text_generation(prompt, max_new_tokens=30, stream=False) print([f"{prompt}\n{generated_output}"]) ``` --------- Co-authored-by: Nicolas Patry <patry.nicolas@protonmail.com>
2024-05-15 22:58:47 -06:00
hf-transfer = ["hf-transfer (>=0.1.4)"]
inference = ["aiohttp", "minijinja (>=1.0)"]
quality = ["mypy (==1.5.1)", "ruff (>=0.3.0)"]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
tensorflow = ["graphviz", "pydot", "tensorflow"]
Pali gemma modeling (#1895) This PR adds paligemma modeling code Blog post: https://huggingface.co/blog/paligemma Transformers PR: https://github.com/huggingface/transformers/pull/30814 install the latest changes and run with ```bash # get the weights # text-generation-server download-weights gv-hf/PaliGemma-base-224px-hf # run TGI text-generation-launcher --model-id gv-hf/PaliGemma-base-224px-hf ``` basic example sending various requests ```python from huggingface_hub import InferenceClient client = InferenceClient("http://127.0.0.1:3000") images = [ "https://huggingface.co/datasets/hf-internal-testing/fixtures-captioning/resolve/main/cow_beach_1.png", "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/transformers/rabbit.png", ] prompts = [ "What animal is in this image?", "Name three colors in this image.", "What are 10 colors in this image?", "Where is the cow standing?", "answer en Where is the cow standing?", "Is there a bird in the image?", "Is ther a cow in the image?", "Is there a rabbit in the image?", "how many birds are in the image?", "how many rabbits are in the image?", ] for img in images: print(f"\nImage: {img.split('/')[-1]}") for prompt in prompts: inputs = f"![]({img}){prompt}\n" json_data = { "inputs": inputs, "parameters": { "max_new_tokens": 30, "do_sample": False, }, } generated_output = client.text_generation(prompt, max_new_tokens=30, stream=False) print([f"{prompt}\n{generated_output}"]) ``` --------- Co-authored-by: Nicolas Patry <patry.nicolas@protonmail.com>
2024-05-15 22:58:47 -06:00
tensorflow-testing = ["keras (<3.0)", "tensorflow"]
testing = ["InquirerPy (==0.3.4)", "Jinja2", "Pillow", "aiohttp", "fastapi", "gradio", "jedi", "minijinja (>=1.0)", "numpy", "pytest", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-rerunfailures", "pytest-vcr", "pytest-xdist", "soundfile", "urllib3 (<2.0)"]
torch = ["safetensors", "torch"]
feat: relax mistral requirements (#1351) Close #1253 Close #1279
2023-12-15 04:52:24 -07:00
typing = ["types-PyYAML", "types-requests", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)"]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
[[package]]
name = "idna"
Updating outlines to 0.0.46
2024-09-13 07:38:38 -06:00
version = "3.8"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
description = "Internationalized Domain Names in Applications (IDNA)"
optional = false
Updating outlines to 0.0.46
2024-09-13 07:38:38 -06:00
python-versions = ">=3.6"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
files = [
Updating outlines to 0.0.46
2024-09-13 07:38:38 -06:00
{file = "idna-3.8-py3-none-any.whl", hash = "sha256:050b4e5baadcd44d760cedbd2b8e639f2ff89bbc7a5730fcc662954303377aac"},
{file = "idna-3.8.tar.gz", hash = "sha256:d838c2c0ed6fced7693d5e8ab8e734d5f8fda53a039c0164afb0b82e771e3603"},
feat(server): use latest flash attention commit (#543) @njhill FYI
2023-07-04 12:23:55 -06:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
Making `make install` work better by default. (#2004) # What does this PR do? Making `make install` a much better sane default to start local dev environments. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-06-04 11:38:46 -06:00
[[package]]
name = "importlib-metadata"
version = "7.1.0"
description = "Read metadata from Python packages"
optional = false
python-versions = ">=3.8"
files = [
{file = "importlib_metadata-7.1.0-py3-none-any.whl", hash = "sha256:30962b96c0c223483ed6cc7280e7f0199feb01a0e40cfae4d4450fc6fab1f570"},
{file = "importlib_metadata-7.1.0.tar.gz", hash = "sha256:b78938b926ee8d5f020fc4772d487045805a55ddbad2ecf21c6d60938dc7fcd2"},
]
[package.dependencies]
zipp = ">=0.5"
[package.extras]
docs = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"]
perf = ["ipython"]
testing = ["flufl.flake8", "importlib-resources (>=1.3)", "jaraco.test (>=5.4)", "packaging", "pyfakefs", "pytest (>=6)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-mypy", "pytest-perf (>=0.9.2)", "pytest-ruff (>=0.2.1)"]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
[[package]]
name = "iniconfig"
version = "2.0.0"
description = "brain-dead simple config-ini parsing"
optional = false
python-versions = ">=3.7"
files = [
feat(server): use latest flash attention commit (#543) @njhill FYI
2023-07-04 12:23:55 -06:00
{file = "iniconfig-2.0.0-py3-none-any.whl", hash = "sha256:b6a85871a79d2e3b22d2d1b94ac2824226a63c6b741c88f7ae975f18b6778374"},
{file = "iniconfig-2.0.0.tar.gz", hash = "sha256:2d91e135bf72d31a410b17c16da610a82cb55f6b0477d1a902134b24a455b8b3"},
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
v1.4.1 (#1568)
2024-02-16 09:50:57 -07:00
[[package]]
name = "interegular"
version = "0.3.3"
description = "a regex intersection checker"
optional = true
python-versions = ">=3.7"
files = [
{file = "interegular-0.3.3-py37-none-any.whl", hash = "sha256:b0c07007d48c89d6d19f7204972d369b2a77222722e126b6aa63aa721dc3b19c"},
{file = "interegular-0.3.3.tar.gz", hash = "sha256:d9b697b21b34884711399ba0f0376914b81899ce670032486d0d048344a76600"},
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
[[package]]
This should prevent the PyTorch overriding. (#767) # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 13:54:39 -06:00
name = "jinja2"
Granite support? (#1882) # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-13 05:46:29 -06:00
version = "3.1.4"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
description = "A very fast and expressive template engine."
chore: update to torch 2.1.0 (#1182) Close #1142
2023-11-23 05:38:50 -07:00
optional = true
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
python-versions = ">=3.7"
files = [
Granite support? (#1882) # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-13 05:46:29 -06:00
{file = "jinja2-3.1.4-py3-none-any.whl", hash = "sha256:bc5dd2abb727a5319567b7a813e6a2e7318c39f4f487cfe6c89c6f9c7d25197d"},
{file = "jinja2-3.1.4.tar.gz", hash = "sha256:4a3aee7acbbe7303aede8e9648d13b8bf88a429282aa6122a993f0ac800cb369"},
feat(server): use latest flash attention commit (#543) @njhill FYI
2023-07-04 12:23:55 -06:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
[package.dependencies]
MarkupSafe = ">=2.0"
[package.extras]
i18n = ["Babel (>=2.7)"]
v1.4.1 (#1568)
2024-02-16 09:50:57 -07:00
[[package]]
name = "jsonschema"
Softcapping for gemma2. (#2273) * Softcapping for gemma2. * Less clutter. * No access to transformers config, only config_dict here. * 0.0 is the null value in the C++ API.
2024-07-22 10:27:10 -06:00
version = "4.23.0"
v1.4.1 (#1568)
2024-02-16 09:50:57 -07:00
description = "An implementation of JSON Schema validation for Python"
optional = true
python-versions = ">=3.8"
files = [
Softcapping for gemma2. (#2273) * Softcapping for gemma2. * Less clutter. * No access to transformers config, only config_dict here. * 0.0 is the null value in the C++ API.
2024-07-22 10:27:10 -06:00
{file = "jsonschema-4.23.0-py3-none-any.whl", hash = "sha256:fbadb6f8b144a8f8cf9f0b89ba94501d143e50411a1278633f56a7acf7fd5566"},
{file = "jsonschema-4.23.0.tar.gz", hash = "sha256:d71497fef26351a33265337fa77ffeb82423f3ea21283cd9467bb03999266bc4"},
v1.4.1 (#1568)
2024-02-16 09:50:57 -07:00
]
[package.dependencies]
attrs = ">=22.2.0"
jsonschema-specifications = ">=2023.03.6"
referencing = ">=0.28.4"
rpds-py = ">=0.7.1"
[package.extras]
format = ["fqdn", "idna", "isoduration", "jsonpointer (>1.13)", "rfc3339-validator", "rfc3987", "uri-template", "webcolors (>=1.11)"]
Softcapping for gemma2. (#2273) * Softcapping for gemma2. * Less clutter. * No access to transformers config, only config_dict here. * 0.0 is the null value in the C++ API.
2024-07-22 10:27:10 -06:00
format-nongpl = ["fqdn", "idna", "isoduration", "jsonpointer (>1.13)", "rfc3339-validator", "rfc3986-validator (>0.1.0)", "uri-template", "webcolors (>=24.6.0)"]
v1.4.1 (#1568)
2024-02-16 09:50:57 -07:00
[[package]]
name = "jsonschema-specifications"
version = "2023.12.1"
description = "The JSON Schema meta-schemas and vocabularies, exposed as a Registry"
optional = true
python-versions = ">=3.8"
files = [
{file = "jsonschema_specifications-2023.12.1-py3-none-any.whl", hash = "sha256:87e4fdf3a94858b8a2ba2778d9ba57d8a9cafca7c7489c46ba0d30a8bc6a9c3c"},
{file = "jsonschema_specifications-2023.12.1.tar.gz", hash = "sha256:48a76787b3e70f5ed53f1160d2b81f586e4ca6d1548c5de7085d1682674764cc"},
]
[package.dependencies]
referencing = ">=0.31.0"
[[package]]
name = "lark"
Updating outlines to 0.0.46
2024-09-13 07:38:38 -06:00
version = "1.2.2"
v1.4.1 (#1568)
2024-02-16 09:50:57 -07:00
description = "a modern parsing library"
optional = true
Updating outlines to 0.0.46
2024-09-13 07:38:38 -06:00
python-versions = ">=3.8"
v1.4.1 (#1568)
2024-02-16 09:50:57 -07:00
files = [
Updating outlines to 0.0.46
2024-09-13 07:38:38 -06:00
{file = "lark-1.2.2-py3-none-any.whl", hash = "sha256:c2276486b02f0f1b90be155f2c8ba4a8e194d42775786db622faccd652d8e80c"},
{file = "lark-1.2.2.tar.gz", hash = "sha256:ca807d0162cd16cef15a8feecb862d7319e7a09bdb13aef927968e45040fed80"},
v1.4.1 (#1568)
2024-02-16 09:50:57 -07:00
]
[package.extras]
atomic-cache = ["atomicwrites"]
interegular = ["interegular (>=0.3.1,<0.4.0)"]
nearley = ["js2py"]
regex = ["regex"]
[[package]]
name = "llvmlite"
Softcapping for gemma2. (#2273) * Softcapping for gemma2. * Less clutter. * No access to transformers config, only config_dict here. * 0.0 is the null value in the C++ API.
2024-07-22 10:27:10 -06:00
version = "0.43.0"
v1.4.1 (#1568)
2024-02-16 09:50:57 -07:00
description = "lightweight wrapper around basic LLVM functionality"
optional = true
python-versions = ">=3.9"
files = [
Softcapping for gemma2. (#2273) * Softcapping for gemma2. * Less clutter. * No access to transformers config, only config_dict here. * 0.0 is the null value in the C++ API.
2024-07-22 10:27:10 -06:00
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v1.4.1 (#1568)
2024-02-16 09:50:57 -07:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
[[package]]
name = "loguru"
version = "0.6.0"
description = "Python logging made (stupidly) simple"
optional = false
python-versions = ">=3.5"
files = [
feat(server): use latest flash attention commit (#543) @njhill FYI
2023-07-04 12:23:55 -06:00
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feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
[package.dependencies]
colorama = {version = ">=0.3.4", markers = "sys_platform == \"win32\""}
win32-setctime = {version = ">=1.0.0", markers = "sys_platform == \"win32\""}
[package.extras]
dev = ["Sphinx (>=4.1.1)", "black (>=19.10b0)", "colorama (>=0.3.4)", "docutils (==0.16)", "flake8 (>=3.7.7)", "isort (>=5.1.1)", "pytest (>=4.6.2)", "pytest-cov (>=2.7.1)", "sphinx-autobuild (>=0.7.1)", "sphinx-rtd-theme (>=0.4.3)", "tox (>=3.9.0)"]
Fixing exl2 and other quanize tests again. (#2419) * Fixing exl2 and other quanize tests again. * Mark exl2 as non release (so CI tests them, needs to be removed latet). * Fixing exl2 (by disabling cuda graphs) * Fix quantization defaults without cuda graphs on exl2 (linked to new issues with it). * Removing serde override. * Go back to released exl2 and remove log. * Adding warnings for deprecated bitsandbytes + upgrade info to warn.
2024-08-15 03:12:51 -06:00
[[package]]
name = "markdown-it-py"
version = "3.0.0"
description = "Python port of markdown-it. Markdown parsing, done right!"
optional = false
python-versions = ">=3.8"
files = [
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[package.dependencies]
mdurl = ">=0.1,<1.0"
[package.extras]
benchmarking = ["psutil", "pytest", "pytest-benchmark"]
code-style = ["pre-commit (>=3.0,<4.0)"]
compare = ["commonmark (>=0.9,<1.0)", "markdown (>=3.4,<4.0)", "mistletoe (>=1.0,<2.0)", "mistune (>=2.0,<3.0)", "panflute (>=2.3,<3.0)"]
linkify = ["linkify-it-py (>=1,<3)"]
plugins = ["mdit-py-plugins"]
profiling = ["gprof2dot"]
rtd = ["jupyter_sphinx", "mdit-py-plugins", "myst-parser", "pyyaml", "sphinx", "sphinx-copybutton", "sphinx-design", "sphinx_book_theme"]
testing = ["coverage", "pytest", "pytest-cov", "pytest-regressions"]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
[[package]]
This should prevent the PyTorch overriding. (#767) # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 13:54:39 -06:00
name = "markupsafe"
v1.4.1 (#1568)
2024-02-16 09:50:57 -07:00
version = "2.1.5"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
description = "Safely add untrusted strings to HTML/XML markup."
chore: update to torch 2.1.0 (#1182) Close #1142
2023-11-23 05:38:50 -07:00
optional = true
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
python-versions = ">=3.7"
files = [
v1.4.1 (#1568)
2024-02-16 09:50:57 -07:00
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feat(server): use latest flash attention commit (#543) @njhill FYI
2023-07-04 12:23:55 -06:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
Install Marlin from standalone package (#2320)
2024-07-29 07:37:10 -06:00
[[package]]
name = "marlin-kernels"
version = "0.2.0"
description = "Marlin quantization kernels"
optional = true
python-versions = ">=3.7"
files = [
{file = "marlin_kernels-0.2.0+cu123torch2.4-cp310-cp310-linux_x86_64.whl", hash = "sha256:9a5afcf19b0f5917e43353cc19873fb3c4d4d0b924e2a95a37884f9ce208d0bd"},
]
[package.dependencies]
torch = "*"
[package.source]
type = "url"
url = "https://github.com/danieldk/marlin-kernels/releases/download/v0.2.0/marlin_kernels-0.2.0+cu123torch2.4-cp310-cp310-linux_x86_64.whl"
[[package]]
name = "marlin-kernels"
version = "0.2.0"
description = "Marlin quantization kernels"
optional = true
python-versions = ">=3.7"
files = [
{file = "marlin_kernels-0.2.0+cu123torch2.4-cp311-cp311-linux_x86_64.whl", hash = "sha256:1e64fcc7ebadfaffa60091ee9201ae3daaf5c1be3be60c8c054143a3dcb72d5d"},
]
[package.dependencies]
torch = "*"
[package.source]
type = "url"
url = "https://github.com/danieldk/marlin-kernels/releases/download/v0.2.0/marlin_kernels-0.2.0+cu123torch2.4-cp311-cp311-linux_x86_64.whl"
[[package]]
name = "marlin-kernels"
version = "0.2.0"
description = "Marlin quantization kernels"
optional = true
python-versions = ">=3.7"
files = [
{file = "marlin_kernels-0.2.0+cu123torch2.4-cp312-cp312-linux_x86_64.whl", hash = "sha256:e75f3ce9b1c13a4ed43a380d88e1d34d297259452db037ec1973ec33dc2eb78e"},
]
[package.dependencies]
torch = "*"
[package.source]
type = "url"
url = "https://github.com/danieldk/marlin-kernels/releases/download/v0.2.0/marlin_kernels-0.2.0+cu123torch2.4-cp312-cp312-linux_x86_64.whl"
[[package]]
name = "marlin-kernels"
version = "0.2.0"
description = "Marlin quantization kernels"
optional = true
python-versions = ">=3.7"
files = [
{file = "marlin_kernels-0.2.0+cu123torch2.4-cp39-cp39-linux_x86_64.whl", hash = "sha256:2f99a27f70b391887ee6adffeeee7c3f4df7fac37393f9fb16d4cace2b3f6457"},
]
[package.dependencies]
torch = "*"
[package.source]
type = "url"
url = "https://github.com/danieldk/marlin-kernels/releases/download/v0.2.0/marlin_kernels-0.2.0+cu123torch2.4-cp39-cp39-linux_x86_64.whl"
Fixing exl2 and other quanize tests again. (#2419) * Fixing exl2 and other quanize tests again. * Mark exl2 as non release (so CI tests them, needs to be removed latet). * Fixing exl2 (by disabling cuda graphs) * Fix quantization defaults without cuda graphs on exl2 (linked to new issues with it). * Removing serde override. * Go back to released exl2 and remove log. * Adding warnings for deprecated bitsandbytes + upgrade info to warn.
2024-08-15 03:12:51 -06:00
[[package]]
name = "mdurl"
version = "0.1.2"
description = "Markdown URL utilities"
optional = false
python-versions = ">=3.7"
files = [
{file = "mdurl-0.1.2-py3-none-any.whl", hash = "sha256:84008a41e51615a49fc9966191ff91509e3c40b939176e643fd50a5c2196b8f8"},
{file = "mdurl-0.1.2.tar.gz", hash = "sha256:bb413d29f5eea38f31dd4754dd7377d4465116fb207585f97bf925588687c1ba"},
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
[[package]]
name = "mpmath"
version = "1.3.0"
description = "Python library for arbitrary-precision floating-point arithmetic"
chore: update to torch 2.1.0 (#1182) Close #1142
2023-11-23 05:38:50 -07:00
optional = true
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
python-versions = "*"
files = [
feat(server): use latest flash attention commit (#543) @njhill FYI
2023-07-04 12:23:55 -06:00
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feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
[package.extras]
develop = ["codecov", "pycodestyle", "pytest (>=4.6)", "pytest-cov", "wheel"]
docs = ["sphinx"]
gmpy = ["gmpy2 (>=2.1.0a4)"]
tests = ["pytest (>=4.6)"]
[[package]]
name = "multidict"
Updating outlines to 0.0.46
2024-09-13 07:38:38 -06:00
version = "6.1.0"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
description = "multidict implementation"
optional = true
Updating outlines to 0.0.46
2024-09-13 07:38:38 -06:00
python-versions = ">=3.8"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
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Updating outlines to 0.0.46
2024-09-13 07:38:38 -06:00
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fix(server): fix missing datasets in quantize
2023-07-27 06:50:45 -06:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
Updating outlines to 0.0.46
2024-09-13 07:38:38 -06:00
[package.dependencies]
typing-extensions = {version = ">=4.1.0", markers = "python_version < \"3.11\""}
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
[[package]]
name = "multiprocess"
Softcapping for gemma2. (#2273) * Softcapping for gemma2. * Less clutter. * No access to transformers config, only config_dict here. * 0.0 is the null value in the C++ API.
2024-07-22 10:27:10 -06:00
version = "0.70.16"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
description = "better multiprocessing and multithreading in Python"
optional = true
Softcapping for gemma2. (#2273) * Softcapping for gemma2. * Less clutter. * No access to transformers config, only config_dict here. * 0.0 is the null value in the C++ API.
2024-07-22 10:27:10 -06:00
python-versions = ">=3.8"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
files = [
Softcapping for gemma2. (#2273) * Softcapping for gemma2. * Less clutter. * No access to transformers config, only config_dict here. * 0.0 is the null value in the C++ API.
2024-07-22 10:27:10 -06:00
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fix(server): fix missing datasets in quantize
2023-07-27 06:50:45 -06:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
[package.dependencies]
Softcapping for gemma2. (#2273) * Softcapping for gemma2. * Less clutter. * No access to transformers config, only config_dict here. * 0.0 is the null value in the C++ API.
2024-07-22 10:27:10 -06:00
dill = ">=0.3.8"
v1.4.1 (#1568)
2024-02-16 09:50:57 -07:00
[[package]]
name = "nest-asyncio"
version = "1.6.0"
description = "Patch asyncio to allow nested event loops"
optional = true
python-versions = ">=3.5"
files = [
{file = "nest_asyncio-1.6.0-py3-none-any.whl", hash = "sha256:87af6efd6b5e897c81050477ef65c62e2b2f35d51703cae01aff2905b1852e1c"},
{file = "nest_asyncio-1.6.0.tar.gz", hash = "sha256:6f172d5449aca15afd6c646851f4e31e02c598d553a667e38cafa997cfec55fe"},
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
[[package]]
name = "networkx"
chore: update to torch 2.1.0 (#1182) Close #1142
2023-11-23 05:38:50 -07:00
version = "3.2.1"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
description = "Python package for creating and manipulating graphs and networks"
chore: update to torch 2.1.0 (#1182) Close #1142
2023-11-23 05:38:50 -07:00
optional = true
python-versions = ">=3.9"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
files = [
chore: update to torch 2.1.0 (#1182) Close #1142
2023-11-23 05:38:50 -07:00
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feat(server): use latest flash attention commit (#543) @njhill FYI
2023-07-04 12:23:55 -06:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
[package.extras]
chore: update to torch 2.1.0 (#1182) Close #1142
2023-11-23 05:38:50 -07:00
default = ["matplotlib (>=3.5)", "numpy (>=1.22)", "pandas (>=1.4)", "scipy (>=1.9,!=1.11.0,!=1.11.1)"]
developer = ["changelist (==0.4)", "mypy (>=1.1)", "pre-commit (>=3.2)", "rtoml"]
doc = ["nb2plots (>=0.7)", "nbconvert (<7.9)", "numpydoc (>=1.6)", "pillow (>=9.4)", "pydata-sphinx-theme (>=0.14)", "sphinx (>=7)", "sphinx-gallery (>=0.14)", "texext (>=0.6.7)"]
extra = ["lxml (>=4.6)", "pydot (>=1.4.2)", "pygraphviz (>=1.11)", "sympy (>=1.10)"]
test = ["pytest (>=7.2)", "pytest-cov (>=4.0)"]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
v1.4.1 (#1568)
2024-02-16 09:50:57 -07:00
[[package]]
name = "numba"
Softcapping for gemma2. (#2273) * Softcapping for gemma2. * Less clutter. * No access to transformers config, only config_dict here. * 0.0 is the null value in the C++ API.
2024-07-22 10:27:10 -06:00
version = "0.60.0"
v1.4.1 (#1568)
2024-02-16 09:50:57 -07:00
description = "compiling Python code using LLVM"
optional = true
python-versions = ">=3.9"
files = [
Softcapping for gemma2. (#2273) * Softcapping for gemma2. * Less clutter. * No access to transformers config, only config_dict here. * 0.0 is the null value in the C++ API.
2024-07-22 10:27:10 -06:00
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v1.4.1 (#1568)
2024-02-16 09:50:57 -07:00
]
[package.dependencies]
Softcapping for gemma2. (#2273) * Softcapping for gemma2. * Less clutter. * No access to transformers config, only config_dict here. * 0.0 is the null value in the C++ API.
2024-07-22 10:27:10 -06:00
llvmlite = "==0.43.*"
numpy = ">=1.22,<2.1"
v1.4.1 (#1568)
2024-02-16 09:50:57 -07:00
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
[[package]]
name = "numpy"
hotfix: pin numpy (#2289)
2024-07-23 09:53:19 -06:00
version = "1.26.4"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
description = "Fundamental package for array computing in Python"
optional = false
chore: update to torch 2.1.0 (#1182) Close #1142
2023-11-23 05:38:50 -07:00
python-versions = ">=3.9"
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hotfix: pin numpy (#2289)
2024-07-23 09:53:19 -06:00
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chore: update to torch 2.1.0 (#1182) Close #1142
2023-11-23 05:38:50 -07:00
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Some small fixes for the Torch 2.4.0 update (#2304) * Fix GPTQ autotune data type to be compatible with Torch 2.4.0 * Update poetry lock file * Fix small PaliGemma logprob differences after the torch update
2024-07-25 05:34:44 -06:00
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chore: update to torch 2.1.0 (#1182) Close #1142
2023-11-23 05:38:50 -07:00
description = "cuDNN runtime libraries"
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python-versions = ">=3"
files = [
Some small fixes for the Torch 2.4.0 update (#2304) * Fix GPTQ autotune data type to be compatible with Torch 2.4.0 * Update poetry lock file * Fix small PaliGemma logprob differences after the torch update
2024-07-25 05:34:44 -06:00
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chore: update to torch 2.1.0 (#1182) Close #1142
2023-11-23 05:38:50 -07:00
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[[package]]
name = "nvidia-nccl-cu12"
(chore): torch 2.3.0 (#1833) # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-04-30 10:15:35 -06:00
version = "2.20.5"
chore: update to torch 2.1.0 (#1182) Close #1142
2023-11-23 05:38:50 -07:00
description = "NVIDIA Collective Communication Library (NCCL) Runtime"
optional = true
python-versions = ">=3"
files = [
(chore): torch 2.3.0 (#1833) # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-04-30 10:15:35 -06:00
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{file = "nvidia_nccl_cu12-2.20.5-py3-none-manylinux2014_x86_64.whl", hash = "sha256:057f6bf9685f75215d0c53bf3ac4a10b3e6578351de307abad9e18a99182af56"},
chore: update to torch 2.1.0 (#1182) Close #1142
2023-11-23 05:38:50 -07:00
]
[[package]]
name = "nvidia-nvjitlink-cu12"
Updating outlines to 0.0.46
2024-09-13 07:38:38 -06:00
version = "12.6.68"
chore: update to torch 2.1.0 (#1182) Close #1142
2023-11-23 05:38:50 -07:00
description = "Nvidia JIT LTO Library"
optional = true
python-versions = ">=3"
files = [
Updating outlines to 0.0.46
2024-09-13 07:38:38 -06:00
{file = "nvidia_nvjitlink_cu12-12.6.68-py3-none-manylinux2014_aarch64.whl", hash = "sha256:b3fd0779845f68b92063ab1393abab1ed0a23412fc520df79a8190d098b5cd6b"},
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{file = "nvidia_nvjitlink_cu12-12.6.68-py3-none-win_amd64.whl", hash = "sha256:a55744c98d70317c5e23db14866a8cc2b733f7324509e941fc96276f9f37801d"},
chore: update to torch 2.1.0 (#1182) Close #1142
2023-11-23 05:38:50 -07:00
]
[[package]]
name = "nvidia-nvtx-cu12"
version = "12.1.105"
description = "NVIDIA Tools Extension"
optional = true
python-versions = ">=3"
files = [
{file = "nvidia_nvtx_cu12-12.1.105-py3-none-manylinux1_x86_64.whl", hash = "sha256:dc21cf308ca5691e7c04d962e213f8a4aa9bbfa23d95412f452254c2caeb09e5"},
{file = "nvidia_nvtx_cu12-12.1.105-py3-none-win_amd64.whl", hash = "sha256:65f4d98982b31b60026e0e6de73fbdfc09d08a96f4656dd3665ca616a11e1e82"},
feat(server): use latest flash attention commit (#543) @njhill FYI
2023-07-04 12:23:55 -06:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
[[package]]
name = "opentelemetry-api"
Making `make install` work better by default. (#2004) # What does this PR do? Making `make install` a much better sane default to start local dev environments. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-06-04 11:38:46 -06:00
version = "1.25.0"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
description = "OpenTelemetry Python API"
optional = false
Making `make install` work better by default. (#2004) # What does this PR do? Making `make install` a much better sane default to start local dev environments. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-06-04 11:38:46 -06:00
python-versions = ">=3.8"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
files = [
Making `make install` work better by default. (#2004) # What does this PR do? Making `make install` a much better sane default to start local dev environments. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-06-04 11:38:46 -06:00
{file = "opentelemetry_api-1.25.0-py3-none-any.whl", hash = "sha256:757fa1aa020a0f8fa139f8959e53dec2051cc26b832e76fa839a6d76ecefd737"},
{file = "opentelemetry_api-1.25.0.tar.gz", hash = "sha256:77c4985f62f2614e42ce77ee4c9da5fa5f0bc1e1821085e9a47533a9323ae869"},
feat(server): use latest flash attention commit (#543) @njhill FYI
2023-07-04 12:23:55 -06:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
[package.dependencies]
deprecated = ">=1.2.6"
Making `make install` work better by default. (#2004) # What does this PR do? Making `make install` a much better sane default to start local dev environments. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-06-04 11:38:46 -06:00
importlib-metadata = ">=6.0,<=7.1"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
[[package]]
name = "opentelemetry-exporter-otlp"
Making `make install` work better by default. (#2004) # What does this PR do? Making `make install` a much better sane default to start local dev environments. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-06-04 11:38:46 -06:00
version = "1.25.0"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
description = "OpenTelemetry Collector Exporters"
optional = false
Making `make install` work better by default. (#2004) # What does this PR do? Making `make install` a much better sane default to start local dev environments. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-06-04 11:38:46 -06:00
python-versions = ">=3.8"
files = [
{file = "opentelemetry_exporter_otlp-1.25.0-py3-none-any.whl", hash = "sha256:d67a831757014a3bc3174e4cd629ae1493b7ba8d189e8a007003cacb9f1a6b60"},
{file = "opentelemetry_exporter_otlp-1.25.0.tar.gz", hash = "sha256:ce03199c1680a845f82e12c0a6a8f61036048c07ec7a0bd943142aca8fa6ced0"},
]
[package.dependencies]
opentelemetry-exporter-otlp-proto-grpc = "1.25.0"
opentelemetry-exporter-otlp-proto-http = "1.25.0"
[[package]]
name = "opentelemetry-exporter-otlp-proto-common"
version = "1.25.0"
description = "OpenTelemetry Protobuf encoding"
optional = false
python-versions = ">=3.8"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
files = [
Making `make install` work better by default. (#2004) # What does this PR do? Making `make install` a much better sane default to start local dev environments. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-06-04 11:38:46 -06:00
{file = "opentelemetry_exporter_otlp_proto_common-1.25.0-py3-none-any.whl", hash = "sha256:15637b7d580c2675f70246563363775b4e6de947871e01d0f4e3881d1848d693"},
{file = "opentelemetry_exporter_otlp_proto_common-1.25.0.tar.gz", hash = "sha256:c93f4e30da4eee02bacd1e004eb82ce4da143a2f8e15b987a9f603e0a85407d3"},
feat(server): use latest flash attention commit (#543) @njhill FYI
2023-07-04 12:23:55 -06:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
[package.dependencies]
Making `make install` work better by default. (#2004) # What does this PR do? Making `make install` a much better sane default to start local dev environments. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-06-04 11:38:46 -06:00
opentelemetry-proto = "1.25.0"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
[[package]]
name = "opentelemetry-exporter-otlp-proto-grpc"
Making `make install` work better by default. (#2004) # What does this PR do? Making `make install` a much better sane default to start local dev environments. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-06-04 11:38:46 -06:00
version = "1.25.0"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
description = "OpenTelemetry Collector Protobuf over gRPC Exporter"
optional = false
Making `make install` work better by default. (#2004) # What does this PR do? Making `make install` a much better sane default to start local dev environments. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-06-04 11:38:46 -06:00
python-versions = ">=3.8"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
files = [
Making `make install` work better by default. (#2004) # What does this PR do? Making `make install` a much better sane default to start local dev environments. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-06-04 11:38:46 -06:00
{file = "opentelemetry_exporter_otlp_proto_grpc-1.25.0-py3-none-any.whl", hash = "sha256:3131028f0c0a155a64c430ca600fd658e8e37043cb13209f0109db5c1a3e4eb4"},
{file = "opentelemetry_exporter_otlp_proto_grpc-1.25.0.tar.gz", hash = "sha256:c0b1661415acec5af87625587efa1ccab68b873745ca0ee96b69bb1042087eac"},
feat(server): use latest flash attention commit (#543) @njhill FYI
2023-07-04 12:23:55 -06:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
[package.dependencies]
Making `make install` work better by default. (#2004) # What does this PR do? Making `make install` a much better sane default to start local dev environments. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-06-04 11:38:46 -06:00
deprecated = ">=1.2.6"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
googleapis-common-protos = ">=1.52,<2.0"
grpcio = ">=1.0.0,<2.0.0"
Making `make install` work better by default. (#2004) # What does this PR do? Making `make install` a much better sane default to start local dev environments. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-06-04 11:38:46 -06:00
opentelemetry-api = ">=1.15,<2.0"
opentelemetry-exporter-otlp-proto-common = "1.25.0"
opentelemetry-proto = "1.25.0"
opentelemetry-sdk = ">=1.25.0,<1.26.0"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
[[package]]
name = "opentelemetry-exporter-otlp-proto-http"
Making `make install` work better by default. (#2004) # What does this PR do? Making `make install` a much better sane default to start local dev environments. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-06-04 11:38:46 -06:00
version = "1.25.0"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
description = "OpenTelemetry Collector Protobuf over HTTP Exporter"
optional = false
Making `make install` work better by default. (#2004) # What does this PR do? Making `make install` a much better sane default to start local dev environments. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-06-04 11:38:46 -06:00
python-versions = ">=3.8"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
files = [
Making `make install` work better by default. (#2004) # What does this PR do? Making `make install` a much better sane default to start local dev environments. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-06-04 11:38:46 -06:00
{file = "opentelemetry_exporter_otlp_proto_http-1.25.0-py3-none-any.whl", hash = "sha256:2eca686ee11b27acd28198b3ea5e5863a53d1266b91cda47c839d95d5e0541a6"},
{file = "opentelemetry_exporter_otlp_proto_http-1.25.0.tar.gz", hash = "sha256:9f8723859e37c75183ea7afa73a3542f01d0fd274a5b97487ea24cb683d7d684"},
feat(server): use latest flash attention commit (#543) @njhill FYI
2023-07-04 12:23:55 -06:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
[package.dependencies]
Making `make install` work better by default. (#2004) # What does this PR do? Making `make install` a much better sane default to start local dev environments. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-06-04 11:38:46 -06:00
deprecated = ">=1.2.6"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
googleapis-common-protos = ">=1.52,<2.0"
Making `make install` work better by default. (#2004) # What does this PR do? Making `make install` a much better sane default to start local dev environments. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-06-04 11:38:46 -06:00
opentelemetry-api = ">=1.15,<2.0"
opentelemetry-exporter-otlp-proto-common = "1.25.0"
opentelemetry-proto = "1.25.0"
opentelemetry-sdk = ">=1.25.0,<1.26.0"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
requests = ">=2.7,<3.0"
[[package]]
name = "opentelemetry-instrumentation"
Making `make install` work better by default. (#2004) # What does this PR do? Making `make install` a much better sane default to start local dev environments. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-06-04 11:38:46 -06:00
version = "0.46b0"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
description = "Instrumentation Tools & Auto Instrumentation for OpenTelemetry Python"
optional = false
Making `make install` work better by default. (#2004) # What does this PR do? Making `make install` a much better sane default to start local dev environments. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-06-04 11:38:46 -06:00
python-versions = ">=3.8"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
files = [
Making `make install` work better by default. (#2004) # What does this PR do? Making `make install` a much better sane default to start local dev environments. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-06-04 11:38:46 -06:00
{file = "opentelemetry_instrumentation-0.46b0-py3-none-any.whl", hash = "sha256:89cd721b9c18c014ca848ccd11181e6b3fd3f6c7669e35d59c48dc527408c18b"},
{file = "opentelemetry_instrumentation-0.46b0.tar.gz", hash = "sha256:974e0888fb2a1e01c38fbacc9483d024bb1132aad92d6d24e2e5543887a7adda"},
feat(server): use latest flash attention commit (#543) @njhill FYI
2023-07-04 12:23:55 -06:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
[package.dependencies]
opentelemetry-api = ">=1.4,<2.0"
setuptools = ">=16.0"
wrapt = ">=1.0.0,<2.0.0"
[[package]]
name = "opentelemetry-instrumentation-grpc"
Making `make install` work better by default. (#2004) # What does this PR do? Making `make install` a much better sane default to start local dev environments. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-06-04 11:38:46 -06:00
version = "0.46b0"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
description = "OpenTelemetry gRPC instrumentation"
optional = false
Making `make install` work better by default. (#2004) # What does this PR do? Making `make install` a much better sane default to start local dev environments. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-06-04 11:38:46 -06:00
python-versions = ">=3.8"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
files = [
Making `make install` work better by default. (#2004) # What does this PR do? Making `make install` a much better sane default to start local dev environments. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-06-04 11:38:46 -06:00
{file = "opentelemetry_instrumentation_grpc-0.46b0-py3-none-any.whl", hash = "sha256:cccfb28db07c28849709f2dcf330237fae0fca9f86971bfce27b28bb9a8b0577"},
{file = "opentelemetry_instrumentation_grpc-0.46b0.tar.gz", hash = "sha256:9c5738592cf82672805099826b676d352324b54e03f9ac72a1368ba0605d6ff9"},
feat(server): use latest flash attention commit (#543) @njhill FYI
2023-07-04 12:23:55 -06:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
[package.dependencies]
opentelemetry-api = ">=1.12,<2.0"
Making `make install` work better by default. (#2004) # What does this PR do? Making `make install` a much better sane default to start local dev environments. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-06-04 11:38:46 -06:00
opentelemetry-instrumentation = "0.46b0"
opentelemetry-semantic-conventions = "0.46b0"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
wrapt = ">=1.0.0,<2.0.0"
[package.extras]
instruments = ["grpcio (>=1.27,<2.0)"]
[[package]]
name = "opentelemetry-proto"
Making `make install` work better by default. (#2004) # What does this PR do? Making `make install` a much better sane default to start local dev environments. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-06-04 11:38:46 -06:00
version = "1.25.0"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
description = "OpenTelemetry Python Proto"
optional = false
Making `make install` work better by default. (#2004) # What does this PR do? Making `make install` a much better sane default to start local dev environments. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-06-04 11:38:46 -06:00
python-versions = ">=3.8"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
files = [
Making `make install` work better by default. (#2004) # What does this PR do? Making `make install` a much better sane default to start local dev environments. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-06-04 11:38:46 -06:00
{file = "opentelemetry_proto-1.25.0-py3-none-any.whl", hash = "sha256:f07e3341c78d835d9b86665903b199893befa5e98866f63d22b00d0b7ca4972f"},
{file = "opentelemetry_proto-1.25.0.tar.gz", hash = "sha256:35b6ef9dc4a9f7853ecc5006738ad40443701e52c26099e197895cbda8b815a3"},
feat(server): use latest flash attention commit (#543) @njhill FYI
2023-07-04 12:23:55 -06:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
[package.dependencies]
protobuf = ">=3.19,<5.0"
[[package]]
name = "opentelemetry-sdk"
Making `make install` work better by default. (#2004) # What does this PR do? Making `make install` a much better sane default to start local dev environments. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-06-04 11:38:46 -06:00
version = "1.25.0"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
description = "OpenTelemetry Python SDK"
optional = false
Making `make install` work better by default. (#2004) # What does this PR do? Making `make install` a much better sane default to start local dev environments. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-06-04 11:38:46 -06:00
python-versions = ">=3.8"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
files = [
Making `make install` work better by default. (#2004) # What does this PR do? Making `make install` a much better sane default to start local dev environments. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-06-04 11:38:46 -06:00
{file = "opentelemetry_sdk-1.25.0-py3-none-any.whl", hash = "sha256:d97ff7ec4b351692e9d5a15af570c693b8715ad78b8aafbec5c7100fe966b4c9"},
{file = "opentelemetry_sdk-1.25.0.tar.gz", hash = "sha256:ce7fc319c57707ef5bf8b74fb9f8ebdb8bfafbe11898410e0d2a761d08a98ec7"},
feat(server): use latest flash attention commit (#543) @njhill FYI
2023-07-04 12:23:55 -06:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
[package.dependencies]
Making `make install` work better by default. (#2004) # What does this PR do? Making `make install` a much better sane default to start local dev environments. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-06-04 11:38:46 -06:00
opentelemetry-api = "1.25.0"
opentelemetry-semantic-conventions = "0.46b0"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
typing-extensions = ">=3.7.4"
[[package]]
name = "opentelemetry-semantic-conventions"
Making `make install` work better by default. (#2004) # What does this PR do? Making `make install` a much better sane default to start local dev environments. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-06-04 11:38:46 -06:00
version = "0.46b0"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
description = "OpenTelemetry Semantic Conventions"
optional = false
Making `make install` work better by default. (#2004) # What does this PR do? Making `make install` a much better sane default to start local dev environments. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-06-04 11:38:46 -06:00
python-versions = ">=3.8"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
files = [
Making `make install` work better by default. (#2004) # What does this PR do? Making `make install` a much better sane default to start local dev environments. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-06-04 11:38:46 -06:00
{file = "opentelemetry_semantic_conventions-0.46b0-py3-none-any.whl", hash = "sha256:6daef4ef9fa51d51855d9f8e0ccd3a1bd59e0e545abe99ac6203804e36ab3e07"},
{file = "opentelemetry_semantic_conventions-0.46b0.tar.gz", hash = "sha256:fbc982ecbb6a6e90869b15c1673be90bd18c8a56ff1cffc0864e38e2edffaefa"},
feat(server): use latest flash attention commit (#543) @njhill FYI
2023-07-04 12:23:55 -06:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
Making `make install` work better by default. (#2004) # What does this PR do? Making `make install` a much better sane default to start local dev environments. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-06-04 11:38:46 -06:00
[package.dependencies]
opentelemetry-api = "1.25.0"
v1.4.1 (#1568)
2024-02-16 09:50:57 -07:00
[[package]]
name = "outlines"
Updating outlines to 0.0.46
2024-09-13 07:38:38 -06:00
version = "0.0.46"
v1.4.1 (#1568)
2024-02-16 09:50:57 -07:00
description = "Probabilistic Generative Model Programming"
optional = true
python-versions = ">=3.8"
files = [
Updating outlines to 0.0.46
2024-09-13 07:38:38 -06:00
{file = "outlines-0.0.46-py3-none-any.whl", hash = "sha256:fea7b2ccd2dd82ddf11849a55ef14c4d7b72f12136a67d1b105b81639c8ca2b0"},
{file = "outlines-0.0.46.tar.gz", hash = "sha256:cd272418a268e0a25b7189180dfdcf9fe1b99f50ac1dfb9ffd83c896c5b3fa3c"},
v1.4.1 (#1568)
2024-02-16 09:50:57 -07:00
]
[package.dependencies]
cloudpickle = "*"
Updating outlines to 0.0.46
2024-09-13 07:38:38 -06:00
datasets = "*"
v1.4.1 (#1568)
2024-02-16 09:50:57 -07:00
diskcache = "*"
interegular = "*"
jinja2 = "*"
jsonschema = "*"
lark = "*"
nest-asyncio = "*"
numba = "*"
Updating outlines to 0.0.46
2024-09-13 07:38:38 -06:00
numpy = "<2.0.0"
pyairports = "*"
pycountry = "*"
v1.4.1 (#1568)
2024-02-16 09:50:57 -07:00
pydantic = ">=2.0"
referencing = "*"
requests = "*"
Updating outlines to 0.0.46
2024-09-13 07:38:38 -06:00
tqdm = "*"
typing-extensions = "*"
v1.4.1 (#1568)
2024-02-16 09:50:57 -07:00
[package.extras]
Updating outlines to 0.0.46
2024-09-13 07:38:38 -06:00
serve = ["fastapi", "pydantic (>=2.0)", "uvicorn", "vllm (>=0.3.0)"]
test = ["accelerate", "beartype (<0.16.0)", "coverage[toml] (>=5.1)", "diff-cover", "huggingface-hub", "llama-cpp-python", "mlx-lm", "openai (>=1.0.0)", "pre-commit", "pytest", "pytest-benchmark", "pytest-cov", "pytest-mock", "responses", "torch", "transformers", "vllm"]
v1.4.1 (#1568)
2024-02-16 09:50:57 -07:00
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
[[package]]
name = "packaging"
Softcapping for gemma2. (#2273) * Softcapping for gemma2. * Less clutter. * No access to transformers config, only config_dict here. * 0.0 is the null value in the C++ API.
2024-07-22 10:27:10 -06:00
version = "24.1"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
description = "Core utilities for Python packages"
optional = false
Softcapping for gemma2. (#2273) * Softcapping for gemma2. * Less clutter. * No access to transformers config, only config_dict here. * 0.0 is the null value in the C++ API.
2024-07-22 10:27:10 -06:00
python-versions = ">=3.8"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
files = [
Softcapping for gemma2. (#2273) * Softcapping for gemma2. * Less clutter. * No access to transformers config, only config_dict here. * 0.0 is the null value in the C++ API.
2024-07-22 10:27:10 -06:00
{file = "packaging-24.1-py3-none-any.whl", hash = "sha256:5b8f2217dbdbd2f7f384c41c628544e6d52f2d0f53c6d0c3ea61aa5d1d7ff124"},
{file = "packaging-24.1.tar.gz", hash = "sha256:026ed72c8ed3fcce5bf8950572258698927fd1dbda10a5e981cdf0ac37f4f002"},
feat(server): use latest flash attention commit (#543) @njhill FYI
2023-07-04 12:23:55 -06:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
[[package]]
name = "pandas"
Upgrading all versions. (#1759)
2024-04-18 09:17:40 -06:00
version = "2.2.2"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
description = "Powerful data structures for data analysis, time series, and statistics"
optional = true
Add AWQ quantization inference support (#1019) (#1054) # Add AWQ quantization inference support Fixes https://github.com/huggingface/text-generation-inference/issues/781 This PR (partially) adds support for AWQ quantization for inference. More information on AWQ [here](https://arxiv.org/abs/2306.00978). In general, AWQ is faster and more accurate than GPTQ, which is currently supported by TGI. This PR installs 4-bit GEMM custom CUDA kernels released by AWQ authors (in `requirements.txt`, just one line change). Quick way to test this PR would be bring up TGI as follows: ``` text-generation-server download-weights abhinavkulkarni/codellama-CodeLlama-7b-Python-hf-w4-g128-awq text-generation-launcher \ --huggingface-hub-cache ~/.cache/huggingface/hub/ \ --model-id abhinavkulkarni/codellama-CodeLlama-7b-Python-hf-w4-g128-awq \ --trust-remote-code --port 8080 \ --max-input-length 2048 --max-total-tokens 4096 --max-batch-prefill-tokens 4096 \ --quantize awq ``` Please note: * This PR was tested with FlashAttention v2 and vLLM. * This PR adds support for AWQ inference, not quantizing the models. That needs to be done outside of TGI, instructions [here](https://github.com/mit-han-lab/llm-awq/tree/f084f40bd996f3cf3a0633c1ad7d9d476c318aaa). * This PR only adds support for `FlashLlama` models for now. * Multi-GPU setup has not been tested. * No integration tests have been added so far, will add later if maintainers are interested in this change. * This PR can be tested on any of the models released [here](https://huggingface.co/abhinavkulkarni?sort_models=downloads#models). Please refer to the linked issue for benchmarks for [abhinavkulkarni/meta-llama-Llama-2-7b-chat-hf-w4-g128-awq](https://huggingface.co/abhinavkulkarni/meta-llama-Llama-2-7b-chat-hf-w4-g128-awq) vs [TheBloke/Llama-2-7b-Chat-GPTQ](https://huggingface.co/TheBloke/Llama-2-7b-Chat-GPTQ). Please note, AWQ has released faster (and in case of Llama, fused) kernels for 4-bit GEMM, currently at the top of the `main` branch at https://github.com/mit-han-lab/llm-awq, but this PR uses an older commit that has been tested to work. We can switch to latest commit later on. ## Who can review? @OlivierDehaene OR @Narsil --------- # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil --> --------- Co-authored-by: Abhinav M Kulkarni <abhinavkulkarni@gmail.com> Co-authored-by: Abhinav Kulkarni <abhinav@concentric.ai>
2023-09-25 07:31:27 -06:00
python-versions = ">=3.9"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
files = [
Upgrading all versions. (#1759)
2024-04-18 09:17:40 -06:00
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fix(server): fix missing datasets in quantize
2023-07-27 06:50:45 -06:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
[package.dependencies]
numpy = [
Upgrading all versions. (#1759)
2024-04-18 09:17:40 -06:00
{version = ">=1.22.4", markers = "python_version < \"3.11\""},
{version = ">=1.23.2", markers = "python_version == \"3.11\""},
{version = ">=1.26.0", markers = "python_version >= \"3.12\""},
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
]
python-dateutil = ">=2.8.2"
pytz = ">=2020.1"
v1.4.0 (#1494)
2024-01-26 11:04:57 -07:00
tzdata = ">=2022.7"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
[package.extras]
v1.4.0 (#1494)
2024-01-26 11:04:57 -07:00
all = ["PyQt5 (>=5.15.9)", "SQLAlchemy (>=2.0.0)", "adbc-driver-postgresql (>=0.8.0)", "adbc-driver-sqlite (>=0.8.0)", "beautifulsoup4 (>=4.11.2)", "bottleneck (>=1.3.6)", "dataframe-api-compat (>=0.1.7)", "fastparquet (>=2022.12.0)", "fsspec (>=2022.11.0)", "gcsfs (>=2022.11.0)", "html5lib (>=1.1)", "hypothesis (>=6.46.1)", "jinja2 (>=3.1.2)", "lxml (>=4.9.2)", "matplotlib (>=3.6.3)", "numba (>=0.56.4)", "numexpr (>=2.8.4)", "odfpy (>=1.4.1)", "openpyxl (>=3.1.0)", "pandas-gbq (>=0.19.0)", "psycopg2 (>=2.9.6)", "pyarrow (>=10.0.1)", "pymysql (>=1.0.2)", "pyreadstat (>=1.2.0)", "pytest (>=7.3.2)", "pytest-xdist (>=2.2.0)", "python-calamine (>=0.1.7)", "pyxlsb (>=1.0.10)", "qtpy (>=2.3.0)", "s3fs (>=2022.11.0)", "scipy (>=1.10.0)", "tables (>=3.8.0)", "tabulate (>=0.9.0)", "xarray (>=2022.12.0)", "xlrd (>=2.0.1)", "xlsxwriter (>=3.0.5)", "zstandard (>=0.19.0)"]
aws = ["s3fs (>=2022.11.0)"]
clipboard = ["PyQt5 (>=5.15.9)", "qtpy (>=2.3.0)"]
compression = ["zstandard (>=0.19.0)"]
computation = ["scipy (>=1.10.0)", "xarray (>=2022.12.0)"]
Add AWQ quantization inference support (#1019) (#1054) # Add AWQ quantization inference support Fixes https://github.com/huggingface/text-generation-inference/issues/781 This PR (partially) adds support for AWQ quantization for inference. More information on AWQ [here](https://arxiv.org/abs/2306.00978). In general, AWQ is faster and more accurate than GPTQ, which is currently supported by TGI. This PR installs 4-bit GEMM custom CUDA kernels released by AWQ authors (in `requirements.txt`, just one line change). Quick way to test this PR would be bring up TGI as follows: ``` text-generation-server download-weights abhinavkulkarni/codellama-CodeLlama-7b-Python-hf-w4-g128-awq text-generation-launcher \ --huggingface-hub-cache ~/.cache/huggingface/hub/ \ --model-id abhinavkulkarni/codellama-CodeLlama-7b-Python-hf-w4-g128-awq \ --trust-remote-code --port 8080 \ --max-input-length 2048 --max-total-tokens 4096 --max-batch-prefill-tokens 4096 \ --quantize awq ``` Please note: * This PR was tested with FlashAttention v2 and vLLM. * This PR adds support for AWQ inference, not quantizing the models. That needs to be done outside of TGI, instructions [here](https://github.com/mit-han-lab/llm-awq/tree/f084f40bd996f3cf3a0633c1ad7d9d476c318aaa). * This PR only adds support for `FlashLlama` models for now. * Multi-GPU setup has not been tested. * No integration tests have been added so far, will add later if maintainers are interested in this change. * This PR can be tested on any of the models released [here](https://huggingface.co/abhinavkulkarni?sort_models=downloads#models). Please refer to the linked issue for benchmarks for [abhinavkulkarni/meta-llama-Llama-2-7b-chat-hf-w4-g128-awq](https://huggingface.co/abhinavkulkarni/meta-llama-Llama-2-7b-chat-hf-w4-g128-awq) vs [TheBloke/Llama-2-7b-Chat-GPTQ](https://huggingface.co/TheBloke/Llama-2-7b-Chat-GPTQ). Please note, AWQ has released faster (and in case of Llama, fused) kernels for 4-bit GEMM, currently at the top of the `main` branch at https://github.com/mit-han-lab/llm-awq, but this PR uses an older commit that has been tested to work. We can switch to latest commit later on. ## Who can review? @OlivierDehaene OR @Narsil --------- # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil --> --------- Co-authored-by: Abhinav M Kulkarni <abhinavkulkarni@gmail.com> Co-authored-by: Abhinav Kulkarni <abhinav@concentric.ai>
2023-09-25 07:31:27 -06:00
consortium-standard = ["dataframe-api-compat (>=0.1.7)"]
v1.4.0 (#1494)
2024-01-26 11:04:57 -07:00
excel = ["odfpy (>=1.4.1)", "openpyxl (>=3.1.0)", "python-calamine (>=0.1.7)", "pyxlsb (>=1.0.10)", "xlrd (>=2.0.1)", "xlsxwriter (>=3.0.5)"]
feather = ["pyarrow (>=10.0.1)"]
fss = ["fsspec (>=2022.11.0)"]
gcp = ["gcsfs (>=2022.11.0)", "pandas-gbq (>=0.19.0)"]
hdf5 = ["tables (>=3.8.0)"]
html = ["beautifulsoup4 (>=4.11.2)", "html5lib (>=1.1)", "lxml (>=4.9.2)"]
mysql = ["SQLAlchemy (>=2.0.0)", "pymysql (>=1.0.2)"]
output-formatting = ["jinja2 (>=3.1.2)", "tabulate (>=0.9.0)"]
parquet = ["pyarrow (>=10.0.1)"]
performance = ["bottleneck (>=1.3.6)", "numba (>=0.56.4)", "numexpr (>=2.8.4)"]
plot = ["matplotlib (>=3.6.3)"]
postgresql = ["SQLAlchemy (>=2.0.0)", "adbc-driver-postgresql (>=0.8.0)", "psycopg2 (>=2.9.6)"]
feat: cohere (#1660)
2024-03-22 10:59:25 -06:00
pyarrow = ["pyarrow (>=10.0.1)"]
v1.4.0 (#1494)
2024-01-26 11:04:57 -07:00
spss = ["pyreadstat (>=1.2.0)"]
sql-other = ["SQLAlchemy (>=2.0.0)", "adbc-driver-postgresql (>=0.8.0)", "adbc-driver-sqlite (>=0.8.0)"]
chore: update to torch 2.1.0 (#1182) Close #1142
2023-11-23 05:38:50 -07:00
test = ["hypothesis (>=6.46.1)", "pytest (>=7.3.2)", "pytest-xdist (>=2.2.0)"]
v1.4.0 (#1494)
2024-01-26 11:04:57 -07:00
xml = ["lxml (>=4.9.2)"]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
[[package]]
name = "peft"
Update libraries (#1713) Co-authored-by: Nicolas Patry <patry.nicolas@protonmail.com>
2024-04-11 02:37:35 -06:00
version = "0.10.0"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
description = "Parameter-Efficient Fine-Tuning (PEFT)"
chore: update to torch 2.1.0 (#1182) Close #1142
2023-11-23 05:38:50 -07:00
optional = true
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
python-versions = ">=3.8.0"
files = [
Update libraries (#1713) Co-authored-by: Nicolas Patry <patry.nicolas@protonmail.com>
2024-04-11 02:37:35 -06:00
{file = "peft-0.10.0-py3-none-any.whl", hash = "sha256:d5249c97e818d3e31f92553c73c2953acd0ec12649b8b749afff7152cbc86cbb"},
{file = "peft-0.10.0.tar.gz", hash = "sha256:36a7628c15f88d37abb26cfc74c22468f9037ee02e9c9b65de943cfe7c672049"},
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
]
[package.dependencies]
Update to peft 0.8.2 (#1537) # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> ## Before submitting - [x] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [x] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [x] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [x] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [x] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. @OlivierDehaene OR @Narsil
2024-02-08 04:44:04 -07:00
accelerate = ">=0.21.0"
huggingface-hub = ">=0.17.0"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
numpy = ">=1.17"
packaging = ">=20.0"
psutil = "*"
pyyaml = "*"
safetensors = "*"
torch = ">=1.13.0"
Update to peft 0.8.2 (#1537) # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> ## Before submitting - [x] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [x] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [x] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [x] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [x] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. @OlivierDehaene OR @Narsil
2024-02-08 04:44:04 -07:00
tqdm = "*"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
transformers = "*"
[package.extras]
feat: cohere (#1660)
2024-03-22 10:59:25 -06:00
dev = ["black", "hf-doc-builder", "ruff (>=0.2.1,<0.3.0)"]
docs-specific = ["black", "hf-doc-builder"]
quality = ["black", "hf-doc-builder", "ruff (>=0.2.1,<0.3.0)"]
test = ["black", "datasets", "diffusers (<0.21.0)", "hf-doc-builder", "parameterized", "pytest", "pytest-cov", "pytest-xdist", "ruff (>=0.2.1,<0.3.0)", "scipy"]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
Adding Idefics multi modal model. (#842) Co-Authored-By: Victor Sanh <victorsanh@gmail.com> # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil --> --------- Co-authored-by: Victor Sanh <victorsanh@gmail.com>
2023-08-17 06:38:49 -06:00
[[package]]
name = "pillow"
Softcapping for gemma2. (#2273) * Softcapping for gemma2. * Less clutter. * No access to transformers config, only config_dict here. * 0.0 is the null value in the C++ API.
2024-07-22 10:27:10 -06:00
version = "10.4.0"
Adding Idefics multi modal model. (#842) Co-Authored-By: Victor Sanh <victorsanh@gmail.com> # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil --> --------- Co-authored-by: Victor Sanh <victorsanh@gmail.com>
2023-08-17 06:38:49 -06:00
description = "Python Imaging Library (Fork)"
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python-versions = ">=3.8"
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Softcapping for gemma2. (#2273) * Softcapping for gemma2. * Less clutter. * No access to transformers config, only config_dict here. * 0.0 is the null value in the C++ API.
2024-07-22 10:27:10 -06:00
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Adding Idefics multi modal model. (#842) Co-Authored-By: Victor Sanh <victorsanh@gmail.com> # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil --> --------- Co-authored-by: Victor Sanh <victorsanh@gmail.com>
2023-08-17 06:38:49 -06:00
]
[package.extras]
Softcapping for gemma2. (#2273) * Softcapping for gemma2. * Less clutter. * No access to transformers config, only config_dict here. * 0.0 is the null value in the C++ API.
2024-07-22 10:27:10 -06:00
docs = ["furo", "olefile", "sphinx (>=7.3)", "sphinx-copybutton", "sphinx-inline-tabs", "sphinxext-opengraph"]
v1.4.0 (#1494)
2024-01-26 11:04:57 -07:00
fpx = ["olefile"]
mic = ["olefile"]
Adding Idefics multi modal model. (#842) Co-Authored-By: Victor Sanh <victorsanh@gmail.com> # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil --> --------- Co-authored-by: Victor Sanh <victorsanh@gmail.com>
2023-08-17 06:38:49 -06:00
tests = ["check-manifest", "coverage", "defusedxml", "markdown2", "olefile", "packaging", "pyroma", "pytest", "pytest-cov", "pytest-timeout"]
v1.4.0 (#1494)
2024-01-26 11:04:57 -07:00
typing = ["typing-extensions"]
xmp = ["defusedxml"]
Adding Idefics multi modal model. (#842) Co-Authored-By: Victor Sanh <victorsanh@gmail.com> # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil --> --------- Co-authored-by: Victor Sanh <victorsanh@gmail.com>
2023-08-17 06:38:49 -06:00
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
[[package]]
name = "pluggy"
(chore): torch 2.3.0 (#1833) # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-04-30 10:15:35 -06:00
version = "1.5.0"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
description = "plugin and hook calling mechanisms for python"
optional = false
New release. (#941) # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-29 06:28:22 -06:00
python-versions = ">=3.8"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
files = [
(chore): torch 2.3.0 (#1833) # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-04-30 10:15:35 -06:00
{file = "pluggy-1.5.0-py3-none-any.whl", hash = "sha256:44e1ad92c8ca002de6377e165f3e0f1be63266ab4d554740532335b9d75ea669"},
{file = "pluggy-1.5.0.tar.gz", hash = "sha256:2cffa88e94fdc978c4c574f15f9e59b7f4201d439195c3715ca9e2486f1d0cf1"},
feat(server): use latest flash attention commit (#543) @njhill FYI
2023-07-04 12:23:55 -06:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
[package.extras]
dev = ["pre-commit", "tox"]
testing = ["pytest", "pytest-benchmark"]
(chore): torch 2.3.0 (#1833) # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-04-30 10:15:35 -06:00
[[package]]
name = "prometheus-client"
version = "0.20.0"
description = "Python client for the Prometheus monitoring system."
optional = false
python-versions = ">=3.8"
files = [
{file = "prometheus_client-0.20.0-py3-none-any.whl", hash = "sha256:cde524a85bce83ca359cc837f28b8c0db5cac7aa653a588fd7e84ba061c329e7"},
{file = "prometheus_client-0.20.0.tar.gz", hash = "sha256:287629d00b147a32dcb2be0b9df905da599b2d82f80377083ec8463309a4bb89"},
]
[package.extras]
twisted = ["twisted"]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
[[package]]
name = "protobuf"
Updating outlines to 0.0.46
2024-09-13 07:38:38 -06:00
version = "4.25.4"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
description = ""
optional = false
chore: update to torch 2.1.0 (#1182) Close #1142
2023-11-23 05:38:50 -07:00
python-versions = ">=3.8"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
files = [
Updating outlines to 0.0.46
2024-09-13 07:38:38 -06:00
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feat(server): use latest flash attention commit (#543) @njhill FYI
2023-07-04 12:23:55 -06:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
[[package]]
name = "psutil"
Softcapping for gemma2. (#2273) * Softcapping for gemma2. * Less clutter. * No access to transformers config, only config_dict here. * 0.0 is the null value in the C++ API.
2024-07-22 10:27:10 -06:00
version = "6.0.0"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
description = "Cross-platform lib for process and system monitoring in Python."
chore: update to torch 2.1.0 (#1182) Close #1142
2023-11-23 05:38:50 -07:00
optional = true
Softcapping for gemma2. (#2273) * Softcapping for gemma2. * Less clutter. * No access to transformers config, only config_dict here. * 0.0 is the null value in the C++ API.
2024-07-22 10:27:10 -06:00
python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,>=2.7"
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feat(server): Add inference support for GPTQ (llama + falcon tested) + Quantization script (#438) Let's start discussing implementation. - Need to expose the quantization scripts (either included here or add doc on how to use https://github.com/qwopqwop200/GPTQ-for-LLaMa) - Make sure GPTQ works for multiple models (priority to Falcon). Currently it means that every place we use `get_{tensor|sharded}` to check for quantization. My idea is to reintegrate as much as possible into `utils/layer.py` by expanding `load_multi` to be a bit more generic. This might require some thinking, but ultimately the `qweight,qzeros,scales,g_idx` should be in a single place, and independant of bias presence. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil --> --------- Co-authored-by: Ubuntu <ubuntu@ip-172-31-41-161.ec2.internal> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2023-06-26 04:27:01 -06:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
[package.extras]
test = ["enum34", "ipaddress", "mock", "pywin32", "wmi"]
(chore): torch 2.3.0 (#1833) # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-04-30 10:15:35 -06:00
[[package]]
name = "py-cpuinfo"
version = "9.0.0"
description = "Get CPU info with pure Python"
optional = false
python-versions = "*"
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]
Updating outlines to 0.0.46
2024-09-13 07:38:38 -06:00
[[package]]
name = "pyairports"
version = "2.1.1"
description = "Airport and other locations database"
optional = true
python-versions = "*"
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feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
[[package]]
name = "pyarrow"
Softcapping for gemma2. (#2273) * Softcapping for gemma2. * Less clutter. * No access to transformers config, only config_dict here. * 0.0 is the null value in the C++ API.
2024-07-22 10:27:10 -06:00
version = "17.0.0"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
description = "Python library for Apache Arrow"
optional = true
New release. (#941) # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-29 06:28:22 -06:00
python-versions = ">=3.8"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
files = [
Softcapping for gemma2. (#2273) * Softcapping for gemma2. * Less clutter. * No access to transformers config, only config_dict here. * 0.0 is the null value in the C++ API.
2024-07-22 10:27:10 -06:00
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fix(server): fix missing datasets in quantize
2023-07-27 06:50:45 -06:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
[package.dependencies]
(chore): torch 2.3.0 (#1833) # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-04-30 10:15:35 -06:00
numpy = ">=1.16.6"
chore: update to torch 2.1.0 (#1182) Close #1142
2023-11-23 05:38:50 -07:00
Softcapping for gemma2. (#2273) * Softcapping for gemma2. * Less clutter. * No access to transformers config, only config_dict here. * 0.0 is the null value in the C++ API.
2024-07-22 10:27:10 -06:00
[package.extras]
test = ["cffi", "hypothesis", "pandas", "pytest", "pytz"]
[[package]]
Updating outlines to 0.0.46
2024-09-13 07:38:38 -06:00
name = "pycountry"
version = "24.6.1"
description = "ISO country, subdivision, language, currency and script definitions and their translations"
Softcapping for gemma2. (#2273) * Softcapping for gemma2. * Less clutter. * No access to transformers config, only config_dict here. * 0.0 is the null value in the C++ API.
2024-07-22 10:27:10 -06:00
optional = true
Updating outlines to 0.0.46
2024-09-13 07:38:38 -06:00
python-versions = ">=3.8"
Softcapping for gemma2. (#2273) * Softcapping for gemma2. * Less clutter. * No access to transformers config, only config_dict here. * 0.0 is the null value in the C++ API.
2024-07-22 10:27:10 -06:00
files = [
Updating outlines to 0.0.46
2024-09-13 07:38:38 -06:00
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Softcapping for gemma2. (#2273) * Softcapping for gemma2. * Less clutter. * No access to transformers config, only config_dict here. * 0.0 is the null value in the C++ API.
2024-07-22 10:27:10 -06:00
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v1.4.1 (#1568)
2024-02-16 09:50:57 -07:00
[[package]]
name = "pydantic"
Updating outlines to 0.0.46
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version = "2.9.1"
v1.4.1 (#1568)
2024-02-16 09:50:57 -07:00
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python-versions = ">=3.8"
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Updating outlines to 0.0.46
2024-09-13 07:38:38 -06:00
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v1.4.1 (#1568)
2024-02-16 09:50:57 -07:00
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[package.dependencies]
Updating outlines to 0.0.46
2024-09-13 07:38:38 -06:00
annotated-types = ">=0.6.0"
pydantic-core = "2.23.3"
Softcapping for gemma2. (#2273) * Softcapping for gemma2. * Less clutter. * No access to transformers config, only config_dict here. * 0.0 is the null value in the C++ API.
2024-07-22 10:27:10 -06:00
typing-extensions = {version = ">=4.6.1", markers = "python_version < \"3.13\""}
v1.4.1 (#1568)
2024-02-16 09:50:57 -07:00
[package.extras]
email = ["email-validator (>=2.0.0)"]
Updating outlines to 0.0.46
2024-09-13 07:38:38 -06:00
timezone = ["tzdata"]
v1.4.1 (#1568)
2024-02-16 09:50:57 -07:00
[[package]]
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Updating outlines to 0.0.46
2024-09-13 07:38:38 -06:00
version = "2.23.3"
Upgrading all versions. (#1759)
2024-04-18 09:17:40 -06:00
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v1.4.1 (#1568)
2024-02-16 09:50:57 -07:00
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Updating outlines to 0.0.46
2024-09-13 07:38:38 -06:00
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v1.4.1 (#1568)
2024-02-16 09:50:57 -07:00
]
[package.dependencies]
typing-extensions = ">=4.6.0,<4.7.0 || >4.7.0"
Fixing exl2 and other quanize tests again. (#2419) * Fixing exl2 and other quanize tests again. * Mark exl2 as non release (so CI tests them, needs to be removed latet). * Fixing exl2 (by disabling cuda graphs) * Fix quantization defaults without cuda graphs on exl2 (linked to new issues with it). * Removing serde override. * Go back to released exl2 and remove log. * Adding warnings for deprecated bitsandbytes + upgrade info to warn.
2024-08-15 03:12:51 -06:00
[[package]]
name = "pygments"
version = "2.18.0"
description = "Pygments is a syntax highlighting package written in Python."
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python-versions = ">=3.8"
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feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
[[package]]
name = "pytest"
v1.4.0 (#1494)
2024-01-26 11:04:57 -07:00
version = "7.4.4"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
description = "pytest: simple powerful testing with Python"
optional = false
python-versions = ">=3.7"
files = [
v1.4.0 (#1494)
2024-01-26 11:04:57 -07:00
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feat(server): Add inference support for GPTQ (llama + falcon tested) + Quantization script (#438) Let's start discussing implementation. - Need to expose the quantization scripts (either included here or add doc on how to use https://github.com/qwopqwop200/GPTQ-for-LLaMa) - Make sure GPTQ works for multiple models (priority to Falcon). Currently it means that every place we use `get_{tensor|sharded}` to check for quantization. My idea is to reintegrate as much as possible into `utils/layer.py` by expanding `load_multi` to be a bit more generic. This might require some thinking, but ultimately the `qweight,qzeros,scales,g_idx` should be in a single place, and independant of bias presence. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil --> --------- Co-authored-by: Ubuntu <ubuntu@ip-172-31-41-161.ec2.internal> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2023-06-26 04:27:01 -06:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
[package.dependencies]
colorama = {version = "*", markers = "sys_platform == \"win32\""}
exceptiongroup = {version = ">=1.0.0rc8", markers = "python_version < \"3.11\""}
iniconfig = "*"
packaging = "*"
pluggy = ">=0.12,<2.0"
tomli = {version = ">=1.0.0", markers = "python_version < \"3.11\""}
[package.extras]
testing = ["argcomplete", "attrs (>=19.2.0)", "hypothesis (>=3.56)", "mock", "nose", "pygments (>=2.7.2)", "requests", "setuptools", "xmlschema"]
[[package]]
name = "python-dateutil"
feat: cohere (#1660)
2024-03-22 10:59:25 -06:00
version = "2.9.0.post0"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
description = "Extensions to the standard Python datetime module"
optional = true
python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,>=2.7"
files = [
feat: cohere (#1660)
2024-03-22 10:59:25 -06:00
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fix(server): fix missing datasets in quantize
2023-07-27 06:50:45 -06:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
[package.dependencies]
six = ">=1.5"
[[package]]
name = "pytz"
Updating outlines to 0.0.46
2024-09-13 07:38:38 -06:00
version = "2024.2"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
description = "World timezone definitions, modern and historical"
optional = true
python-versions = "*"
files = [
Updating outlines to 0.0.46
2024-09-13 07:38:38 -06:00
{file = "pytz-2024.2-py2.py3-none-any.whl", hash = "sha256:31c7c1817eb7fae7ca4b8c7ee50c72f93aa2dd863de768e1ef4245d426aa0725"},
{file = "pytz-2024.2.tar.gz", hash = "sha256:2aa355083c50a0f93fa581709deac0c9ad65cca8a9e9beac660adcbd493c798a"},
fix(server): fix missing datasets in quantize
2023-07-27 06:50:45 -06:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
[[package]]
This should prevent the PyTorch overriding. (#767) # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 13:54:39 -06:00
name = "pyyaml"
Updating outlines to 0.0.46
2024-09-13 07:38:38 -06:00
version = "6.0.2"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
description = "YAML parser and emitter for Python"
optional = false
Updating outlines to 0.0.46
2024-09-13 07:38:38 -06:00
python-versions = ">=3.8"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
files = [
Updating outlines to 0.0.46
2024-09-13 07:38:38 -06:00
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Init
2022-10-08 04:30:12 -06:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
v1.4.1 (#1568)
2024-02-16 09:50:57 -07:00
[[package]]
name = "referencing"
Granite support? (#1882) # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-13 05:46:29 -06:00
version = "0.35.1"
v1.4.1 (#1568)
2024-02-16 09:50:57 -07:00
description = "JSON Referencing + Python"
optional = true
python-versions = ">=3.8"
files = [
Granite support? (#1882) # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-13 05:46:29 -06:00
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{file = "referencing-0.35.1.tar.gz", hash = "sha256:25b42124a6c8b632a425174f24087783efb348a6f1e0008e63cd4466fedf703c"},
v1.4.1 (#1568)
2024-02-16 09:50:57 -07:00
]
[package.dependencies]
attrs = ">=22.2.0"
rpds-py = ">=0.7.0"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
[[package]]
name = "regex"
Updating outlines to 0.0.46
2024-09-13 07:38:38 -06:00
version = "2024.9.11"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
description = "Alternative regular expression module, to replace re."
optional = false
(chore): torch 2.3.0 (#1833) # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-04-30 10:15:35 -06:00
python-versions = ">=3.8"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
files = [
Updating outlines to 0.0.46
2024-09-13 07:38:38 -06:00
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feat(server): Add inference support for GPTQ (llama + falcon tested) + Quantization script (#438) Let's start discussing implementation. - Need to expose the quantization scripts (either included here or add doc on how to use https://github.com/qwopqwop200/GPTQ-for-LLaMa) - Make sure GPTQ works for multiple models (priority to Falcon). Currently it means that every place we use `get_{tensor|sharded}` to check for quantization. My idea is to reintegrate as much as possible into `utils/layer.py` by expanding `load_multi` to be a bit more generic. This might require some thinking, but ultimately the `qweight,qzeros,scales,g_idx` should be in a single place, and independant of bias presence. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil --> --------- Co-authored-by: Ubuntu <ubuntu@ip-172-31-41-161.ec2.internal> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2023-06-26 04:27:01 -06:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
[[package]]
name = "requests"
Making `make install` work better by default. (#2004) # What does this PR do? Making `make install` a much better sane default to start local dev environments. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-06-04 11:38:46 -06:00
version = "2.32.3"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
description = "Python HTTP for Humans."
optional = false
Fix seeded output. (#1949) # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-24 07:36:13 -06:00
python-versions = ">=3.8"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
files = [
Making `make install` work better by default. (#2004) # What does this PR do? Making `make install` a much better sane default to start local dev environments. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-06-04 11:38:46 -06:00
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feat: add distributed tracing (#62)
2023-02-13 05:02:45 -07:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
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charset-normalizer = ">=2,<4"
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urllib3 = ">=1.21.1,<3"
[package.extras]
socks = ["PySocks (>=1.5.6,!=1.5.7)"]
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Fixing exl2 and other quanize tests again. (#2419) * Fixing exl2 and other quanize tests again. * Mark exl2 as non release (so CI tests them, needs to be removed latet). * Fixing exl2 (by disabling cuda graphs) * Fix quantization defaults without cuda graphs on exl2 (linked to new issues with it). * Removing serde override. * Go back to released exl2 and remove log. * Adding warnings for deprecated bitsandbytes + upgrade info to warn.
2024-08-15 03:12:51 -06:00
[[package]]
name = "rich"
Updating outlines to 0.0.46
2024-09-13 07:38:38 -06:00
version = "13.8.1"
Fixing exl2 and other quanize tests again. (#2419) * Fixing exl2 and other quanize tests again. * Mark exl2 as non release (so CI tests them, needs to be removed latet). * Fixing exl2 (by disabling cuda graphs) * Fix quantization defaults without cuda graphs on exl2 (linked to new issues with it). * Removing serde override. * Go back to released exl2 and remove log. * Adding warnings for deprecated bitsandbytes + upgrade info to warn.
2024-08-15 03:12:51 -06:00
description = "Render rich text, tables, progress bars, syntax highlighting, markdown and more to the terminal"
optional = false
python-versions = ">=3.7.0"
files = [
Updating outlines to 0.0.46
2024-09-13 07:38:38 -06:00
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Fixing exl2 and other quanize tests again. (#2419) * Fixing exl2 and other quanize tests again. * Mark exl2 as non release (so CI tests them, needs to be removed latet). * Fixing exl2 (by disabling cuda graphs) * Fix quantization defaults without cuda graphs on exl2 (linked to new issues with it). * Removing serde override. * Go back to released exl2 and remove log. * Adding warnings for deprecated bitsandbytes + upgrade info to warn.
2024-08-15 03:12:51 -06:00
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markdown-it-py = ">=2.2.0"
pygments = ">=2.13.0,<3.0.0"
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jupyter = ["ipywidgets (>=7.5.1,<9)"]
v1.4.1 (#1568)
2024-02-16 09:50:57 -07:00
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name = "rpds-py"
Updating outlines to 0.0.46
2024-09-13 07:38:38 -06:00
version = "0.20.0"
v1.4.1 (#1568)
2024-02-16 09:50:57 -07:00
description = "Python bindings to Rust's persistent data structures (rpds)"
optional = true
python-versions = ">=3.8"
files = [
Updating outlines to 0.0.46
2024-09-13 07:38:38 -06:00
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v1.4.1 (#1568)
2024-02-16 09:50:57 -07:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
[[package]]
name = "safetensors"
Updating outlines to 0.0.46
2024-09-13 07:38:38 -06:00
version = "0.4.5"
feat: cohere (#1660)
2024-03-22 10:59:25 -06:00
description = ""
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
optional = false
feat: cohere (#1660)
2024-03-22 10:59:25 -06:00
python-versions = ">=3.7"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
files = [
Updating outlines to 0.0.46
2024-09-13 07:38:38 -06:00
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feat(server): Improved doc
2022-11-07 04:53:56 -07:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
[package.extras]
feat: cohere (#1660)
2024-03-22 10:59:25 -06:00
all = ["safetensors[jax]", "safetensors[numpy]", "safetensors[paddlepaddle]", "safetensors[pinned-tf]", "safetensors[quality]", "safetensors[testing]", "safetensors[torch]"]
dev = ["safetensors[all]"]
jax = ["flax (>=0.6.3)", "jax (>=0.3.25)", "jaxlib (>=0.3.25)", "safetensors[numpy]"]
mlx = ["mlx (>=0.0.9)"]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
numpy = ["numpy (>=1.21.6)"]
feat: cohere (#1660)
2024-03-22 10:59:25 -06:00
paddlepaddle = ["paddlepaddle (>=2.4.1)", "safetensors[numpy]"]
pinned-tf = ["safetensors[numpy]", "tensorflow (==2.11.0)"]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
quality = ["black (==22.3)", "click (==8.0.4)", "flake8 (>=3.8.3)", "isort (>=5.5.4)"]
feat: cohere (#1660)
2024-03-22 10:59:25 -06:00
tensorflow = ["safetensors[numpy]", "tensorflow (>=2.11.0)"]
Upgrading all versions. (#1759)
2024-04-18 09:17:40 -06:00
testing = ["h5py (>=3.7.0)", "huggingface-hub (>=0.12.1)", "hypothesis (>=6.70.2)", "pytest (>=7.2.0)", "pytest-benchmark (>=4.0.0)", "safetensors[numpy]", "setuptools-rust (>=1.5.2)"]
feat: cohere (#1660)
2024-03-22 10:59:25 -06:00
torch = ["safetensors[numpy]", "torch (>=1.10)"]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
Merge BNB 4bit. (#770) # What does this PR do? See #626 <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil --> --------- Co-authored-by: krzim <zimmerk4@live.com>
2023-08-03 15:00:59 -06:00
[[package]]
name = "scipy"
Fix seeded output. (#1949) # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-24 07:36:13 -06:00
version = "1.13.1"
Merge BNB 4bit. (#770) # What does this PR do? See #626 <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil --> --------- Co-authored-by: krzim <zimmerk4@live.com>
2023-08-03 15:00:59 -06:00
description = "Fundamental algorithms for scientific computing in Python"
optional = false
chore: update to torch 2.1.0 (#1182) Close #1142
2023-11-23 05:38:50 -07:00
python-versions = ">=3.9"
files = [
Fix seeded output. (#1949) # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-24 07:36:13 -06:00
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Merge BNB 4bit. (#770) # What does this PR do? See #626 <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil --> --------- Co-authored-by: krzim <zimmerk4@live.com>
2023-08-03 15:00:59 -06:00
]
[package.dependencies]
Update libraries (#1713) Co-authored-by: Nicolas Patry <patry.nicolas@protonmail.com>
2024-04-11 02:37:35 -06:00
numpy = ">=1.22.4,<2.3"
Merge BNB 4bit. (#770) # What does this PR do? See #626 <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil --> --------- Co-authored-by: krzim <zimmerk4@live.com>
2023-08-03 15:00:59 -06:00
[package.extras]
Update libraries (#1713) Co-authored-by: Nicolas Patry <patry.nicolas@protonmail.com>
2024-04-11 02:37:35 -06:00
dev = ["cython-lint (>=0.12.2)", "doit (>=0.36.0)", "mypy", "pycodestyle", "pydevtool", "rich-click", "ruff", "types-psutil", "typing_extensions"]
doc = ["jupyterlite-pyodide-kernel", "jupyterlite-sphinx (>=0.12.0)", "jupytext", "matplotlib (>=3.5)", "myst-nb", "numpydoc", "pooch", "pydata-sphinx-theme (>=0.15.2)", "sphinx (>=5.0.0)", "sphinx-design (>=0.4.0)"]
test = ["array-api-strict", "asv", "gmpy2", "hypothesis (>=6.30)", "mpmath", "pooch", "pytest", "pytest-cov", "pytest-timeout", "pytest-xdist", "scikit-umfpack", "threadpoolctl"]
Merge BNB 4bit. (#770) # What does this PR do? See #626 <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil --> --------- Co-authored-by: krzim <zimmerk4@live.com>
2023-08-03 15:00:59 -06:00
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
[[package]]
name = "sentencepiece"
version = "0.1.99"
description = "SentencePiece python wrapper"
optional = false
python-versions = "*"
files = [
chore(sever): update requirements (#357) Fixes #338
2023-05-23 10:03:22 -06:00
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feat(server): add flash attention llama (#144)
2023-04-11 08:38:22 -06:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
[[package]]
name = "setuptools"
Updating outlines to 0.0.46
2024-09-13 07:38:38 -06:00
version = "74.1.2"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
description = "Easily download, build, install, upgrade, and uninstall Python packages"
optional = false
New release. (#941) # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-29 06:28:22 -06:00
python-versions = ">=3.8"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
files = [
Updating outlines to 0.0.46
2024-09-13 07:38:38 -06:00
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fix(ci): fix CVE in github-slug-action (#174)
2023-04-13 04:43:05 -06:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
[package.extras]
Updating outlines to 0.0.46
2024-09-13 07:38:38 -06:00
check = ["pytest-checkdocs (>=2.4)", "pytest-ruff (>=0.2.1)", "ruff (>=0.5.2)"]
core = ["importlib-metadata (>=6)", "importlib-resources (>=5.10.2)", "jaraco.text (>=3.7)", "more-itertools (>=8.8)", "packaging (>=24)", "platformdirs (>=2.6.2)", "tomli (>=2.0.1)", "wheel (>=0.43.0)"]
cover = ["pytest-cov"]
doc = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "pygments-github-lexers (==0.0.5)", "pyproject-hooks (!=1.1)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-favicon", "sphinx-inline-tabs", "sphinx-lint", "sphinx-notfound-page (>=1,<2)", "sphinx-reredirects", "sphinxcontrib-towncrier", "towncrier (<24.7)"]
enabler = ["pytest-enabler (>=2.2)"]
test = ["build[virtualenv] (>=1.0.3)", "filelock (>=3.4.0)", "ini2toml[lite] (>=0.14)", "jaraco.develop (>=7.21)", "jaraco.envs (>=2.2)", "jaraco.path (>=3.2.0)", "jaraco.test", "packaging (>=23.2)", "pip (>=19.1)", "pyproject-hooks (!=1.1)", "pytest (>=6,!=8.1.*)", "pytest-home (>=0.5)", "pytest-perf", "pytest-subprocess", "pytest-timeout", "pytest-xdist (>=3)", "tomli-w (>=1.0.0)", "virtualenv (>=13.0.0)", "wheel (>=0.44.0)"]
type = ["importlib-metadata (>=7.0.2)", "jaraco.develop (>=7.21)", "mypy (==1.11.*)", "pytest-mypy"]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
[[package]]
name = "six"
version = "1.16.0"
description = "Python 2 and 3 compatibility utilities"
optional = true
python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*"
files = [
fix(server): fix missing datasets in quantize
2023-07-27 06:50:45 -06:00
{file = "six-1.16.0-py2.py3-none-any.whl", hash = "sha256:8abb2f1d86890a2dfb989f9a77cfcfd3e47c2a354b01111771326f8aa26e0254"},
{file = "six-1.16.0.tar.gz", hash = "sha256:1e61c37477a1626458e36f7b1d82aa5c9b094fa4802892072e49de9c60c4c926"},
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
[[package]]
name = "sympy"
Updating outlines to 0.0.46
2024-09-13 07:38:38 -06:00
version = "1.13.2"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
description = "Computer algebra system (CAS) in Python"
chore: update to torch 2.1.0 (#1182) Close #1142
2023-11-23 05:38:50 -07:00
optional = true
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
python-versions = ">=3.8"
files = [
Updating outlines to 0.0.46
2024-09-13 07:38:38 -06:00
{file = "sympy-1.13.2-py3-none-any.whl", hash = "sha256:c51d75517712f1aed280d4ce58506a4a88d635d6b5dd48b39102a7ae1f3fcfe9"},
{file = "sympy-1.13.2.tar.gz", hash = "sha256:401449d84d07be9d0c7a46a64bd54fe097667d5e7181bfe67ec777be9e01cb13"},
Init
2022-10-08 04:30:12 -06:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
[package.dependencies]
Softcapping for gemma2. (#2273) * Softcapping for gemma2. * Less clutter. * No access to transformers config, only config_dict here. * 0.0 is the null value in the C++ API.
2024-07-22 10:27:10 -06:00
mpmath = ">=1.1.0,<1.4"
[package.extras]
dev = ["hypothesis (>=6.70.0)", "pytest (>=7.1.0)"]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
[[package]]
name = "texttable"
Prepare for v1.1.1 (#1100) # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-10-05 08:09:49 -06:00
version = "1.7.0"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
description = "module to create simple ASCII tables"
optional = true
python-versions = "*"
files = [
Prepare for v1.1.1 (#1100) # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-10-05 08:09:49 -06:00
{file = "texttable-1.7.0-py2.py3-none-any.whl", hash = "sha256:72227d592c82b3d7f672731ae73e4d1f88cd8e2ef5b075a7a7f01a23a3743917"},
{file = "texttable-1.7.0.tar.gz", hash = "sha256:2d2068fb55115807d3ac77a4ca68fa48803e84ebb0ee2340f858107a36522638"},
fix(server): fix quantization python requirements (#708)
2023-07-27 04:28:10 -06:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
[[package]]
name = "tokenizers"
Upgrading all versions. (#1759)
2024-04-18 09:17:40 -06:00
version = "0.19.1"
feat: relax mistral requirements (#1351) Close #1253 Close #1279
2023-12-15 04:52:24 -07:00
description = ""
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
optional = false
feat: relax mistral requirements (#1351) Close #1253 Close #1279
2023-12-15 04:52:24 -07:00
python-versions = ">=3.7"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
files = [
Upgrading all versions. (#1759)
2024-04-18 09:17:40 -06:00
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feat(server): add flash attention llama (#144)
2023-04-11 08:38:22 -06:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
feat: relax mistral requirements (#1351) Close #1253 Close #1279
2023-12-15 04:52:24 -07:00
[package.dependencies]
Upgrading all versions. (#1759)
2024-04-18 09:17:40 -06:00
huggingface-hub = ">=0.16.4,<1.0"
feat: relax mistral requirements (#1351) Close #1253 Close #1279
2023-12-15 04:52:24 -07:00
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
[package.extras]
feat: relax mistral requirements (#1351) Close #1253 Close #1279
2023-12-15 04:52:24 -07:00
dev = ["tokenizers[testing]"]
Upgrading all versions. (#1759)
2024-04-18 09:17:40 -06:00
docs = ["setuptools-rust", "sphinx", "sphinx-rtd-theme"]
testing = ["black (==22.3)", "datasets", "numpy", "pytest", "requests", "ruff"]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
[[package]]
name = "tomli"
version = "2.0.1"
description = "A lil' TOML parser"
optional = false
python-versions = ">=3.7"
files = [
feat(server): Add model tests (#6)
2022-12-08 10:49:33 -07:00
{file = "tomli-2.0.1-py3-none-any.whl", hash = "sha256:939de3e7a6161af0c887ef91b7d41a53e7c5a1ca976325f429cb46ea9bc30ecc"},
{file = "tomli-2.0.1.tar.gz", hash = "sha256:de526c12914f0c550d15924c62d72abc48d6fe7364aa87328337a31007fe8a4f"},
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
[[package]]
name = "torch"
Updating outlines to 0.0.46
2024-09-13 07:38:38 -06:00
version = "2.4.1"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
description = "Tensors and Dynamic neural networks in Python with strong GPU acceleration"
chore: update to torch 2.1.0 (#1182) Close #1142
2023-11-23 05:38:50 -07:00
optional = true
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
python-versions = ">=3.8.0"
files = [
Updating outlines to 0.0.46
2024-09-13 07:38:38 -06:00
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fix(ci): fix CVE in github-slug-action (#174)
2023-04-13 04:43:05 -06:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
[package.dependencies]
filelock = "*"
chore: update to torch 2.1.0 (#1182) Close #1142
2023-11-23 05:38:50 -07:00
fsspec = "*"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
jinja2 = "*"
networkx = "*"
chore: update to torch 2.1.0 (#1182) Close #1142
2023-11-23 05:38:50 -07:00
nvidia-cublas-cu12 = {version = "12.1.3.1", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
nvidia-cuda-cupti-cu12 = {version = "12.1.105", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
nvidia-cuda-nvrtc-cu12 = {version = "12.1.105", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
nvidia-cuda-runtime-cu12 = {version = "12.1.105", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
Some small fixes for the Torch 2.4.0 update (#2304) * Fix GPTQ autotune data type to be compatible with Torch 2.4.0 * Update poetry lock file * Fix small PaliGemma logprob differences after the torch update
2024-07-25 05:34:44 -06:00
nvidia-cudnn-cu12 = {version = "9.1.0.70", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
chore: update to torch 2.1.0 (#1182) Close #1142
2023-11-23 05:38:50 -07:00
nvidia-cufft-cu12 = {version = "11.0.2.54", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
nvidia-curand-cu12 = {version = "10.3.2.106", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
nvidia-cusolver-cu12 = {version = "11.4.5.107", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
nvidia-cusparse-cu12 = {version = "12.1.0.106", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
(chore): torch 2.3.0 (#1833) # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-04-30 10:15:35 -06:00
nvidia-nccl-cu12 = {version = "2.20.5", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
chore: update to torch 2.1.0 (#1182) Close #1142
2023-11-23 05:38:50 -07:00
nvidia-nvtx-cu12 = {version = "12.1.105", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
Updating outlines to 0.0.46
2024-09-13 07:38:38 -06:00
setuptools = "*"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
sympy = "*"
Some small fixes for the Torch 2.4.0 update (#2304) * Fix GPTQ autotune data type to be compatible with Torch 2.4.0 * Update poetry lock file * Fix small PaliGemma logprob differences after the torch update
2024-07-25 05:34:44 -06:00
triton = {version = "3.0.0", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\" and python_version < \"3.13\""}
v1.4.1 (#1568)
2024-02-16 09:50:57 -07:00
typing-extensions = ">=4.8.0"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
[package.extras]
opt-einsum = ["opt-einsum (>=3.3)"]
Some small fixes for the Torch 2.4.0 update (#2304) * Fix GPTQ autotune data type to be compatible with Torch 2.4.0 * Update poetry lock file * Fix small PaliGemma logprob differences after the torch update
2024-07-25 05:34:44 -06:00
optree = ["optree (>=0.11.0)"]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
[[package]]
name = "tqdm"
Updating outlines to 0.0.46
2024-09-13 07:38:38 -06:00
version = "4.66.5"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
description = "Fast, Extensible Progress Meter"
optional = false
python-versions = ">=3.7"
files = [
Updating outlines to 0.0.46
2024-09-13 07:38:38 -06:00
{file = "tqdm-4.66.5-py3-none-any.whl", hash = "sha256:90279a3770753eafc9194a0364852159802111925aa30eb3f9d85b0e805ac7cd"},
{file = "tqdm-4.66.5.tar.gz", hash = "sha256:e1020aef2e5096702d8a025ac7d16b1577279c9d63f8375b63083e9a5f0fcbad"},
fix(server): fix hf_transfer issue with private repos (#203)
2023-04-19 09:36:16 -06:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
[package.dependencies]
colorama = {version = "*", markers = "platform_system == \"Windows\""}
[package.extras]
Adding Idefics multi modal model. (#842) Co-Authored-By: Victor Sanh <victorsanh@gmail.com> # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil --> --------- Co-authored-by: Victor Sanh <victorsanh@gmail.com>
2023-08-17 06:38:49 -06:00
dev = ["pytest (>=6)", "pytest-cov", "pytest-timeout", "pytest-xdist"]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
notebook = ["ipywidgets (>=6)"]
slack = ["slack-sdk"]
telegram = ["requests"]
[[package]]
name = "transformers"
Updating outlines to 0.0.46
2024-09-13 07:38:38 -06:00
version = "4.44.2"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
description = "State-of-the-art Machine Learning for JAX, PyTorch and TensorFlow"
optional = false
Upgrade transformers (fix protobuf==3.20 issue) (#795) # What does this PR do? Fixes #531 <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-11 08:46:08 -06:00
python-versions = ">=3.8.0"
Fix seeded output. (#1949) # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-24 07:36:13 -06:00
files = [
Updating outlines to 0.0.46
2024-09-13 07:38:38 -06:00
{file = "transformers-4.44.2-py3-none-any.whl", hash = "sha256:1c02c65e7bfa5e52a634aff3da52138b583fc6f263c1f28d547dc144ba3d412d"},
{file = "transformers-4.44.2.tar.gz", hash = "sha256:36aa17cc92ee154058e426d951684a2dab48751b35b49437896f898931270826"},
Fix seeded output. (#1949) # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-24 07:36:13 -06:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
[package.dependencies]
filelock = "*"
Softcapping for gemma2. (#2273) * Softcapping for gemma2. * Less clutter. * No access to transformers config, only config_dict here. * 0.0 is the null value in the C++ API.
2024-07-22 10:27:10 -06:00
huggingface-hub = ">=0.23.2,<1.0"
Add support for Llama 3 rotary embeddings (#2286) * Add support for Llama 3 rotary embeddings * Update transformers to 4.43
2024-07-23 09:18:54 -06:00
numpy = ">=1.17"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
packaging = ">=20.0"
pyyaml = ">=5.1"
regex = "!=2019.12.17"
requests = "*"
feat: cohere (#1660)
2024-03-22 10:59:25 -06:00
safetensors = ">=0.4.1"
Upgrading all versions. (#1759)
2024-04-18 09:17:40 -06:00
tokenizers = ">=0.19,<0.20"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
tqdm = ">=4.27"
[package.extras]
feat: relax mistral requirements (#1351) Close #1253 Close #1279
2023-12-15 04:52:24 -07:00
accelerate = ["accelerate (>=0.21.0)"]
feat: cohere (#1660)
2024-03-22 10:59:25 -06:00
agents = ["Pillow (>=10.0.1,<=15.0)", "accelerate (>=0.21.0)", "datasets (!=2.5.0)", "diffusers", "opencv-python", "sentencepiece (>=0.1.91,!=0.1.92)", "torch"]
Add support for Llama 3 rotary embeddings (#2286) * Add support for Llama 3 rotary embeddings * Update transformers to 4.43
2024-07-23 09:18:54 -06:00
all = ["Pillow (>=10.0.1,<=15.0)", "accelerate (>=0.21.0)", "av (==9.2.0)", "codecarbon (==1.2.0)", "decord (==0.6.0)", "flax (>=0.4.1,<=0.7.0)", "jax (>=0.4.1,<=0.4.13)", "jaxlib (>=0.4.1,<=0.4.13)", "kenlm", "keras-nlp (>=0.3.1,<0.14.0)", "librosa", "onnxconverter-common", "optax (>=0.0.8,<=0.1.4)", "optuna", "phonemizer", "protobuf", "pyctcdecode (>=0.4.0)", "ray[tune] (>=2.7.0)", "scipy (<1.13.0)", "sentencepiece (>=0.1.91,!=0.1.92)", "sigopt", "tensorflow (>2.9,<2.16)", "tensorflow-text (<2.16)", "tf2onnx", "timm (<=0.9.16)", "tokenizers (>=0.19,<0.20)", "torch", "torchaudio", "torchvision"]
Upgrade transformers (fix protobuf==3.20 issue) (#795) # What does this PR do? Fixes #531 <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-11 08:46:08 -06:00
audio = ["kenlm", "librosa", "phonemizer", "pyctcdecode (>=0.4.0)"]
Softcapping for gemma2. (#2273) * Softcapping for gemma2. * Less clutter. * No access to transformers config, only config_dict here. * 0.0 is the null value in the C++ API.
2024-07-22 10:27:10 -06:00
benchmark = ["optimum-benchmark (>=0.2.0)"]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
codecarbon = ["codecarbon (==1.2.0)"]
feat: relax mistral requirements (#1351) Close #1253 Close #1279
2023-12-15 04:52:24 -07:00
deepspeed = ["accelerate (>=0.21.0)", "deepspeed (>=0.9.3)"]
Updating outlines to 0.0.46
2024-09-13 07:38:38 -06:00
deepspeed-testing = ["GitPython (<3.1.19)", "accelerate (>=0.21.0)", "beautifulsoup4", "cookiecutter (==1.7.3)", "datasets (!=2.5.0)", "deepspeed (>=0.9.3)", "dill (<0.3.5)", "evaluate (>=0.2.0)", "faiss-cpu", "nltk", "optuna", "parameterized", "protobuf", "psutil", "pydantic", "pytest (>=7.2.0,<8.0.0)", "pytest-rich", "pytest-timeout", "pytest-xdist", "rjieba", "rouge-score (!=0.0.7,!=0.0.8,!=0.1,!=0.1.1)", "ruff (==0.5.1)", "sacrebleu (>=1.4.12,<2.0.0)", "sacremoses", "sentencepiece (>=0.1.91,!=0.1.92)", "tensorboard", "timeout-decorator"]
dev = ["GitPython (<3.1.19)", "Pillow (>=10.0.1,<=15.0)", "accelerate (>=0.21.0)", "av (==9.2.0)", "beautifulsoup4", "codecarbon (==1.2.0)", "cookiecutter (==1.7.3)", "datasets (!=2.5.0)", "decord (==0.6.0)", "dill (<0.3.5)", "evaluate (>=0.2.0)", "faiss-cpu", "flax (>=0.4.1,<=0.7.0)", "fugashi (>=1.0)", "ipadic (>=1.0.0,<2.0)", "isort (>=5.5.4)", "jax (>=0.4.1,<=0.4.13)", "jaxlib (>=0.4.1,<=0.4.13)", "kenlm", "keras-nlp (>=0.3.1,<0.14.0)", "librosa", "nltk", "onnxconverter-common", "optax (>=0.0.8,<=0.1.4)", "optuna", "parameterized", "phonemizer", "protobuf", "psutil", "pyctcdecode (>=0.4.0)", "pydantic", "pytest (>=7.2.0,<8.0.0)", "pytest-rich", "pytest-timeout", "pytest-xdist", "ray[tune] (>=2.7.0)", "rhoknp (>=1.1.0,<1.3.1)", "rjieba", "rouge-score (!=0.0.7,!=0.0.8,!=0.1,!=0.1.1)", "ruff (==0.5.1)", "sacrebleu (>=1.4.12,<2.0.0)", "sacremoses", "scikit-learn", "scipy (<1.13.0)", "sentencepiece (>=0.1.91,!=0.1.92)", "sigopt", "sudachidict-core (>=20220729)", "sudachipy (>=0.6.6)", "tensorboard", "tensorflow (>2.9,<2.16)", "tensorflow-text (<2.16)", "tf2onnx", "timeout-decorator", "timm (<=0.9.16)", "tokenizers (>=0.19,<0.20)", "torch", "torchaudio", "torchvision", "unidic (>=1.0.2)", "unidic-lite (>=1.0.7)", "urllib3 (<2.0.0)"]
dev-tensorflow = ["GitPython (<3.1.19)", "Pillow (>=10.0.1,<=15.0)", "beautifulsoup4", "cookiecutter (==1.7.3)", "datasets (!=2.5.0)", "dill (<0.3.5)", "evaluate (>=0.2.0)", "faiss-cpu", "isort (>=5.5.4)", "kenlm", "keras-nlp (>=0.3.1,<0.14.0)", "librosa", "nltk", "onnxconverter-common", "onnxruntime (>=1.4.0)", "onnxruntime-tools (>=1.4.2)", "parameterized", "phonemizer", "protobuf", "psutil", "pyctcdecode (>=0.4.0)", "pydantic", "pytest (>=7.2.0,<8.0.0)", "pytest-rich", "pytest-timeout", "pytest-xdist", "rjieba", "rouge-score (!=0.0.7,!=0.0.8,!=0.1,!=0.1.1)", "ruff (==0.5.1)", "sacrebleu (>=1.4.12,<2.0.0)", "sacremoses", "scikit-learn", "sentencepiece (>=0.1.91,!=0.1.92)", "tensorboard", "tensorflow (>2.9,<2.16)", "tensorflow-text (<2.16)", "tf2onnx", "timeout-decorator", "tokenizers (>=0.19,<0.20)", "urllib3 (<2.0.0)"]
dev-torch = ["GitPython (<3.1.19)", "Pillow (>=10.0.1,<=15.0)", "accelerate (>=0.21.0)", "beautifulsoup4", "codecarbon (==1.2.0)", "cookiecutter (==1.7.3)", "datasets (!=2.5.0)", "dill (<0.3.5)", "evaluate (>=0.2.0)", "faiss-cpu", "fugashi (>=1.0)", "ipadic (>=1.0.0,<2.0)", "isort (>=5.5.4)", "kenlm", "librosa", "nltk", "onnxruntime (>=1.4.0)", "onnxruntime-tools (>=1.4.2)", "optuna", "parameterized", "phonemizer", "protobuf", "psutil", "pyctcdecode (>=0.4.0)", "pydantic", "pytest (>=7.2.0,<8.0.0)", "pytest-rich", "pytest-timeout", "pytest-xdist", "ray[tune] (>=2.7.0)", "rhoknp (>=1.1.0,<1.3.1)", "rjieba", "rouge-score (!=0.0.7,!=0.0.8,!=0.1,!=0.1.1)", "ruff (==0.5.1)", "sacrebleu (>=1.4.12,<2.0.0)", "sacremoses", "scikit-learn", "sentencepiece (>=0.1.91,!=0.1.92)", "sigopt", "sudachidict-core (>=20220729)", "sudachipy (>=0.6.6)", "tensorboard", "timeout-decorator", "timm (<=0.9.16)", "tokenizers (>=0.19,<0.20)", "torch", "torchaudio", "torchvision", "unidic (>=1.0.2)", "unidic-lite (>=1.0.7)", "urllib3 (<2.0.0)"]
Pali gemma modeling (#1895) This PR adds paligemma modeling code Blog post: https://huggingface.co/blog/paligemma Transformers PR: https://github.com/huggingface/transformers/pull/30814 install the latest changes and run with ```bash # get the weights # text-generation-server download-weights gv-hf/PaliGemma-base-224px-hf # run TGI text-generation-launcher --model-id gv-hf/PaliGemma-base-224px-hf ``` basic example sending various requests ```python from huggingface_hub import InferenceClient client = InferenceClient("http://127.0.0.1:3000") images = [ "https://huggingface.co/datasets/hf-internal-testing/fixtures-captioning/resolve/main/cow_beach_1.png", "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/transformers/rabbit.png", ] prompts = [ "What animal is in this image?", "Name three colors in this image.", "What are 10 colors in this image?", "Where is the cow standing?", "answer en Where is the cow standing?", "Is there a bird in the image?", "Is ther a cow in the image?", "Is there a rabbit in the image?", "how many birds are in the image?", "how many rabbits are in the image?", ] for img in images: print(f"\nImage: {img.split('/')[-1]}") for prompt in prompts: inputs = f"![]({img}){prompt}\n" json_data = { "inputs": inputs, "parameters": { "max_new_tokens": 30, "do_sample": False, }, } generated_output = client.text_generation(prompt, max_new_tokens=30, stream=False) print([f"{prompt}\n{generated_output}"]) ``` --------- Co-authored-by: Nicolas Patry <patry.nicolas@protonmail.com>
2024-05-15 22:58:47 -06:00
flax = ["flax (>=0.4.1,<=0.7.0)", "jax (>=0.4.1,<=0.4.13)", "jaxlib (>=0.4.1,<=0.4.13)", "optax (>=0.0.8,<=0.1.4)", "scipy (<1.13.0)"]
Upgrade transformers (fix protobuf==3.20 issue) (#795) # What does this PR do? Fixes #531 <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-11 08:46:08 -06:00
flax-speech = ["kenlm", "librosa", "phonemizer", "pyctcdecode (>=0.4.0)"]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
ftfy = ["ftfy"]
feat: relax mistral requirements (#1351) Close #1253 Close #1279
2023-12-15 04:52:24 -07:00
integrations = ["optuna", "ray[tune] (>=2.7.0)", "sigopt"]
Fix seeded output. (#1949) # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-24 07:36:13 -06:00
ja = ["fugashi (>=1.0)", "ipadic (>=1.0.0,<2.0)", "rhoknp (>=1.1.0,<1.3.1)", "sudachidict-core (>=20220729)", "sudachipy (>=0.6.6)", "unidic (>=1.0.2)", "unidic-lite (>=1.0.7)"]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
modelcreation = ["cookiecutter (==1.7.3)"]
v1.4.0 (#1494)
2024-01-26 11:04:57 -07:00
natten = ["natten (>=0.14.6,<0.15.0)"]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
onnx = ["onnxconverter-common", "onnxruntime (>=1.4.0)", "onnxruntime-tools (>=1.4.2)", "tf2onnx"]
onnxruntime = ["onnxruntime (>=1.4.0)", "onnxruntime-tools (>=1.4.2)"]
optuna = ["optuna"]
Updating outlines to 0.0.46
2024-09-13 07:38:38 -06:00
quality = ["GitPython (<3.1.19)", "datasets (!=2.5.0)", "isort (>=5.5.4)", "ruff (==0.5.1)", "urllib3 (<2.0.0)"]
feat: relax mistral requirements (#1351) Close #1253 Close #1279
2023-12-15 04:52:24 -07:00
ray = ["ray[tune] (>=2.7.0)"]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
retrieval = ["datasets (!=2.5.0)", "faiss-cpu"]
Updating outlines to 0.0.46
2024-09-13 07:38:38 -06:00
ruff = ["ruff (==0.5.1)"]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
sagemaker = ["sagemaker (>=2.31.0)"]
Upgrade transformers (fix protobuf==3.20 issue) (#795) # What does this PR do? Fixes #531 <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-11 08:46:08 -06:00
sentencepiece = ["protobuf", "sentencepiece (>=0.1.91,!=0.1.92)"]
feat: cohere (#1660)
2024-03-22 10:59:25 -06:00
serving = ["fastapi", "pydantic", "starlette", "uvicorn"]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
sigopt = ["sigopt"]
sklearn = ["scikit-learn"]
Upgrade transformers (fix protobuf==3.20 issue) (#795) # What does this PR do? Fixes #531 <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-11 08:46:08 -06:00
speech = ["kenlm", "librosa", "phonemizer", "pyctcdecode (>=0.4.0)", "torchaudio"]
Updating outlines to 0.0.46
2024-09-13 07:38:38 -06:00
testing = ["GitPython (<3.1.19)", "beautifulsoup4", "cookiecutter (==1.7.3)", "datasets (!=2.5.0)", "dill (<0.3.5)", "evaluate (>=0.2.0)", "faiss-cpu", "nltk", "parameterized", "psutil", "pydantic", "pytest (>=7.2.0,<8.0.0)", "pytest-rich", "pytest-timeout", "pytest-xdist", "rjieba", "rouge-score (!=0.0.7,!=0.0.8,!=0.1,!=0.1.1)", "ruff (==0.5.1)", "sacrebleu (>=1.4.12,<2.0.0)", "sacremoses", "sentencepiece (>=0.1.91,!=0.1.92)", "tensorboard", "timeout-decorator"]
Add support for Llama 3 rotary embeddings (#2286) * Add support for Llama 3 rotary embeddings * Update transformers to 4.43
2024-07-23 09:18:54 -06:00
tf = ["keras-nlp (>=0.3.1,<0.14.0)", "onnxconverter-common", "tensorflow (>2.9,<2.16)", "tensorflow-text (<2.16)", "tf2onnx"]
tf-cpu = ["keras (>2.9,<2.16)", "keras-nlp (>=0.3.1,<0.14.0)", "onnxconverter-common", "tensorflow-cpu (>2.9,<2.16)", "tensorflow-probability (<0.24)", "tensorflow-text (<2.16)", "tf2onnx"]
Upgrade transformers (fix protobuf==3.20 issue) (#795) # What does this PR do? Fixes #531 <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-11 08:46:08 -06:00
tf-speech = ["kenlm", "librosa", "phonemizer", "pyctcdecode (>=0.4.0)"]
Softcapping for gemma2. (#2273) * Softcapping for gemma2. * Less clutter. * No access to transformers config, only config_dict here. * 0.0 is the null value in the C++ API.
2024-07-22 10:27:10 -06:00
timm = ["timm (<=0.9.16)"]
Upgrading all versions. (#1759)
2024-04-18 09:17:40 -06:00
tokenizers = ["tokenizers (>=0.19,<0.20)"]
feat: cohere (#1660)
2024-03-22 10:59:25 -06:00
torch = ["accelerate (>=0.21.0)", "torch"]
Upgrade transformers (fix protobuf==3.20 issue) (#795) # What does this PR do? Fixes #531 <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-11 08:46:08 -06:00
torch-speech = ["kenlm", "librosa", "phonemizer", "pyctcdecode (>=0.4.0)", "torchaudio"]
feat: relax mistral requirements (#1351) Close #1253 Close #1279
2023-12-15 04:52:24 -07:00
torch-vision = ["Pillow (>=10.0.1,<=15.0)", "torchvision"]
Add support for Llama 3 rotary embeddings (#2286) * Add support for Llama 3 rotary embeddings * Update transformers to 4.43
2024-07-23 09:18:54 -06:00
torchhub = ["filelock", "huggingface-hub (>=0.23.2,<1.0)", "importlib-metadata", "numpy (>=1.17)", "packaging (>=20.0)", "protobuf", "regex (!=2019.12.17)", "requests", "sentencepiece (>=0.1.91,!=0.1.92)", "tokenizers (>=0.19,<0.20)", "torch", "tqdm (>=4.27)"]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
video = ["av (==9.2.0)", "decord (==0.6.0)"]
feat: relax mistral requirements (#1351) Close #1253 Close #1279
2023-12-15 04:52:24 -07:00
vision = ["Pillow (>=10.0.1,<=15.0)"]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
chore: update to torch 2.1.0 (#1182) Close #1142
2023-11-23 05:38:50 -07:00
[[package]]
name = "triton"
Some small fixes for the Torch 2.4.0 update (#2304) * Fix GPTQ autotune data type to be compatible with Torch 2.4.0 * Update poetry lock file * Fix small PaliGemma logprob differences after the torch update
2024-07-25 05:34:44 -06:00
version = "3.0.0"
chore: update to torch 2.1.0 (#1182) Close #1142
2023-11-23 05:38:50 -07:00
description = "A language and compiler for custom Deep Learning operations"
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python-versions = "*"
files = [
Some small fixes for the Torch 2.4.0 update (#2304) * Fix GPTQ autotune data type to be compatible with Torch 2.4.0 * Update poetry lock file * Fix small PaliGemma logprob differences after the torch update
2024-07-25 05:34:44 -06:00
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Updating outlines to 0.0.46
2024-09-13 07:38:38 -06:00
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chore: update to torch 2.1.0 (#1182) Close #1142
2023-11-23 05:38:50 -07:00
]
[package.dependencies]
filelock = "*"
[package.extras]
v1.4.1 (#1568)
2024-02-16 09:50:57 -07:00
build = ["cmake (>=3.20)", "lit"]
Some small fixes for the Torch 2.4.0 update (#2304) * Fix GPTQ autotune data type to be compatible with Torch 2.4.0 * Update poetry lock file * Fix small PaliGemma logprob differences after the torch update
2024-07-25 05:34:44 -06:00
tests = ["autopep8", "flake8", "isort", "llnl-hatchet", "numpy", "pytest", "scipy (>=1.7.1)"]
tutorials = ["matplotlib", "pandas", "tabulate"]
chore: update to torch 2.1.0 (#1182) Close #1142
2023-11-23 05:38:50 -07:00
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
[[package]]
name = "typer"
version = "0.6.1"
description = "Typer, build great CLIs. Easy to code. Based on Python type hints."
optional = false
python-versions = ">=3.6"
files = [
Init
2022-10-08 04:30:12 -06:00
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feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
[package.dependencies]
click = ">=7.1.1,<9.0.0"
[package.extras]
all = ["colorama (>=0.4.3,<0.5.0)", "rich (>=10.11.0,<13.0.0)", "shellingham (>=1.3.0,<2.0.0)"]
dev = ["autoflake (>=1.3.1,<2.0.0)", "flake8 (>=3.8.3,<4.0.0)", "pre-commit (>=2.17.0,<3.0.0)"]
doc = ["mdx-include (>=1.4.1,<2.0.0)", "mkdocs (>=1.1.2,<2.0.0)", "mkdocs-material (>=8.1.4,<9.0.0)"]
test = ["black (>=22.3.0,<23.0.0)", "coverage (>=5.2,<6.0)", "isort (>=5.0.6,<6.0.0)", "mypy (==0.910)", "pytest (>=4.4.0,<5.4.0)", "pytest-cov (>=2.10.0,<3.0.0)", "pytest-sugar (>=0.9.4,<0.10.0)", "pytest-xdist (>=1.32.0,<2.0.0)", "rich (>=10.11.0,<13.0.0)", "shellingham (>=1.3.0,<2.0.0)"]
[[package]]
name = "typing-extensions"
Softcapping for gemma2. (#2273) * Softcapping for gemma2. * Less clutter. * No access to transformers config, only config_dict here. * 0.0 is the null value in the C++ API.
2024-07-22 10:27:10 -06:00
version = "4.12.2"
Add AWQ quantization inference support (#1019) (#1054) # Add AWQ quantization inference support Fixes https://github.com/huggingface/text-generation-inference/issues/781 This PR (partially) adds support for AWQ quantization for inference. More information on AWQ [here](https://arxiv.org/abs/2306.00978). In general, AWQ is faster and more accurate than GPTQ, which is currently supported by TGI. This PR installs 4-bit GEMM custom CUDA kernels released by AWQ authors (in `requirements.txt`, just one line change). Quick way to test this PR would be bring up TGI as follows: ``` text-generation-server download-weights abhinavkulkarni/codellama-CodeLlama-7b-Python-hf-w4-g128-awq text-generation-launcher \ --huggingface-hub-cache ~/.cache/huggingface/hub/ \ --model-id abhinavkulkarni/codellama-CodeLlama-7b-Python-hf-w4-g128-awq \ --trust-remote-code --port 8080 \ --max-input-length 2048 --max-total-tokens 4096 --max-batch-prefill-tokens 4096 \ --quantize awq ``` Please note: * This PR was tested with FlashAttention v2 and vLLM. * This PR adds support for AWQ inference, not quantizing the models. That needs to be done outside of TGI, instructions [here](https://github.com/mit-han-lab/llm-awq/tree/f084f40bd996f3cf3a0633c1ad7d9d476c318aaa). * This PR only adds support for `FlashLlama` models for now. * Multi-GPU setup has not been tested. * No integration tests have been added so far, will add later if maintainers are interested in this change. * This PR can be tested on any of the models released [here](https://huggingface.co/abhinavkulkarni?sort_models=downloads#models). Please refer to the linked issue for benchmarks for [abhinavkulkarni/meta-llama-Llama-2-7b-chat-hf-w4-g128-awq](https://huggingface.co/abhinavkulkarni/meta-llama-Llama-2-7b-chat-hf-w4-g128-awq) vs [TheBloke/Llama-2-7b-Chat-GPTQ](https://huggingface.co/TheBloke/Llama-2-7b-Chat-GPTQ). Please note, AWQ has released faster (and in case of Llama, fused) kernels for 4-bit GEMM, currently at the top of the `main` branch at https://github.com/mit-han-lab/llm-awq, but this PR uses an older commit that has been tested to work. We can switch to latest commit later on. ## Who can review? @OlivierDehaene OR @Narsil --------- # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil --> --------- Co-authored-by: Abhinav M Kulkarni <abhinavkulkarni@gmail.com> Co-authored-by: Abhinav Kulkarni <abhinav@concentric.ai>
2023-09-25 07:31:27 -06:00
description = "Backported and Experimental Type Hints for Python 3.8+"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
optional = false
Add AWQ quantization inference support (#1019) (#1054) # Add AWQ quantization inference support Fixes https://github.com/huggingface/text-generation-inference/issues/781 This PR (partially) adds support for AWQ quantization for inference. More information on AWQ [here](https://arxiv.org/abs/2306.00978). In general, AWQ is faster and more accurate than GPTQ, which is currently supported by TGI. This PR installs 4-bit GEMM custom CUDA kernels released by AWQ authors (in `requirements.txt`, just one line change). Quick way to test this PR would be bring up TGI as follows: ``` text-generation-server download-weights abhinavkulkarni/codellama-CodeLlama-7b-Python-hf-w4-g128-awq text-generation-launcher \ --huggingface-hub-cache ~/.cache/huggingface/hub/ \ --model-id abhinavkulkarni/codellama-CodeLlama-7b-Python-hf-w4-g128-awq \ --trust-remote-code --port 8080 \ --max-input-length 2048 --max-total-tokens 4096 --max-batch-prefill-tokens 4096 \ --quantize awq ``` Please note: * This PR was tested with FlashAttention v2 and vLLM. * This PR adds support for AWQ inference, not quantizing the models. That needs to be done outside of TGI, instructions [here](https://github.com/mit-han-lab/llm-awq/tree/f084f40bd996f3cf3a0633c1ad7d9d476c318aaa). * This PR only adds support for `FlashLlama` models for now. * Multi-GPU setup has not been tested. * No integration tests have been added so far, will add later if maintainers are interested in this change. * This PR can be tested on any of the models released [here](https://huggingface.co/abhinavkulkarni?sort_models=downloads#models). Please refer to the linked issue for benchmarks for [abhinavkulkarni/meta-llama-Llama-2-7b-chat-hf-w4-g128-awq](https://huggingface.co/abhinavkulkarni/meta-llama-Llama-2-7b-chat-hf-w4-g128-awq) vs [TheBloke/Llama-2-7b-Chat-GPTQ](https://huggingface.co/TheBloke/Llama-2-7b-Chat-GPTQ). Please note, AWQ has released faster (and in case of Llama, fused) kernels for 4-bit GEMM, currently at the top of the `main` branch at https://github.com/mit-han-lab/llm-awq, but this PR uses an older commit that has been tested to work. We can switch to latest commit later on. ## Who can review? @OlivierDehaene OR @Narsil --------- # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil --> --------- Co-authored-by: Abhinav M Kulkarni <abhinavkulkarni@gmail.com> Co-authored-by: Abhinav Kulkarni <abhinav@concentric.ai>
2023-09-25 07:31:27 -06:00
python-versions = ">=3.8"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
files = [
Softcapping for gemma2. (#2273) * Softcapping for gemma2. * Less clutter. * No access to transformers config, only config_dict here. * 0.0 is the null value in the C++ API.
2024-07-22 10:27:10 -06:00
{file = "typing_extensions-4.12.2-py3-none-any.whl", hash = "sha256:04e5ca0351e0f3f85c6853954072df659d0d13fac324d0072316b67d7794700d"},
{file = "typing_extensions-4.12.2.tar.gz", hash = "sha256:1a7ead55c7e559dd4dee8856e3a88b41225abfe1ce8df57b7c13915fe121ffb8"},
Init
2022-10-08 04:30:12 -06:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
[[package]]
name = "tzdata"
v1.4.1 (#1568)
2024-02-16 09:50:57 -07:00
version = "2024.1"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
description = "Provider of IANA time zone data"
optional = true
python-versions = ">=2"
files = [
v1.4.1 (#1568)
2024-02-16 09:50:57 -07:00
{file = "tzdata-2024.1-py2.py3-none-any.whl", hash = "sha256:9068bc196136463f5245e51efda838afa15aaeca9903f49050dfa2679db4d252"},
{file = "tzdata-2024.1.tar.gz", hash = "sha256:2674120f8d891909751c38abcdfd386ac0a5a1127954fbc332af6b5ceae07efd"},
fix(server): fix missing datasets in quantize
2023-07-27 06:50:45 -06:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
[[package]]
name = "urllib3"
Updating outlines to 0.0.46
2024-09-13 07:38:38 -06:00
version = "2.2.3"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
description = "HTTP library with thread-safe connection pooling, file post, and more."
optional = false
chore: update to torch 2.1.0 (#1182) Close #1142
2023-11-23 05:38:50 -07:00
python-versions = ">=3.8"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
files = [
Updating outlines to 0.0.46
2024-09-13 07:38:38 -06:00
{file = "urllib3-2.2.3-py3-none-any.whl", hash = "sha256:ca899ca043dcb1bafa3e262d73aa25c465bfb49e0bd9dd5d59f1d0acba2f8fac"},
{file = "urllib3-2.2.3.tar.gz", hash = "sha256:e7d814a81dad81e6caf2ec9fdedb284ecc9c73076b62654547cc64ccdcae26e9"},
feat(launcher): Log server stdout (#19) Co-authored-by: Nick Hill <nickhill@us.ibm.com>
2023-01-05 04:01:23 -07:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
[package.extras]
brotli = ["brotli (>=1.0.9)", "brotlicffi (>=0.8.0)"]
v1.4.1 (#1568)
2024-02-16 09:50:57 -07:00
h2 = ["h2 (>=4,<5)"]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
socks = ["pysocks (>=1.5.6,!=1.5.7,<2.0)"]
zstd = ["zstandard (>=0.18.0)"]
[[package]]
name = "win32-setctime"
version = "1.1.0"
description = "A small Python utility to set file creation time on Windows"
optional = false
python-versions = ">=3.5"
files = [
feat(launcher): Log server stdout (#19) Co-authored-by: Nick Hill <nickhill@us.ibm.com>
2023-01-05 04:01:23 -07:00
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feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
[package.extras]
dev = ["black (>=19.3b0)", "pytest (>=4.6.2)"]
[[package]]
name = "wrapt"
chore: update to torch 2.1.0 (#1182) Close #1142
2023-11-23 05:38:50 -07:00
version = "1.16.0"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
description = "Module for decorators, wrappers and monkey patching."
optional = false
chore: update to torch 2.1.0 (#1182) Close #1142
2023-11-23 05:38:50 -07:00
python-versions = ">=3.6"
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feat: add distributed tracing (#62)
2023-02-13 05:02:45 -07:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
[[package]]
name = "xxhash"
Updating outlines to 0.0.46
2024-09-13 07:38:38 -06:00
version = "3.5.0"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
description = "Python binding for xxHash"
optional = true
This should prevent the PyTorch overriding. (#767) # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 13:54:39 -06:00
python-versions = ">=3.7"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
files = [
Updating outlines to 0.0.46
2024-09-13 07:38:38 -06:00
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fix(server): fix missing datasets in quantize
2023-07-27 06:50:45 -06:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
[[package]]
name = "yarl"
Updating outlines to 0.0.46
2024-09-13 07:38:38 -06:00
version = "1.11.1"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
description = "Yet another URL library"
optional = true
Updating outlines to 0.0.46
2024-09-13 07:38:38 -06:00
python-versions = ">=3.8"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
files = [
Updating outlines to 0.0.46
2024-09-13 07:38:38 -06:00
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fix(server): fix missing datasets in quantize
2023-07-27 06:50:45 -06:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
[package.dependencies]
idna = ">=2.0"
multidict = ">=4.0"
Making `make install` work better by default. (#2004) # What does this PR do? Making `make install` a much better sane default to start local dev environments. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-06-04 11:38:46 -06:00
[[package]]
name = "zipp"
Updating outlines to 0.0.46
2024-09-13 07:38:38 -06:00
version = "3.20.1"
Making `make install` work better by default. (#2004) # What does this PR do? Making `make install` a much better sane default to start local dev environments. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-06-04 11:38:46 -06:00
description = "Backport of pathlib-compatible object wrapper for zip files"
optional = false
python-versions = ">=3.8"
files = [
Updating outlines to 0.0.46
2024-09-13 07:38:38 -06:00
{file = "zipp-3.20.1-py3-none-any.whl", hash = "sha256:9960cd8967c8f85a56f920d5d507274e74f9ff813a0ab8889a5b5be2daf44064"},
{file = "zipp-3.20.1.tar.gz", hash = "sha256:c22b14cc4763c5a5b04134207736c107db42e9d3ef2d9779d465f5f1bcba572b"},
Making `make install` work better by default. (#2004) # What does this PR do? Making `make install` a much better sane default to start local dev environments. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-06-04 11:38:46 -06:00
]
[package.extras]
Updating outlines to 0.0.46
2024-09-13 07:38:38 -06:00
check = ["pytest-checkdocs (>=2.4)", "pytest-ruff (>=0.2.1)"]
cover = ["pytest-cov"]
Making `make install` work better by default. (#2004) # What does this PR do? Making `make install` a much better sane default to start local dev environments. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-06-04 11:38:46 -06:00
doc = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"]
Updating outlines to 0.0.46
2024-09-13 07:38:38 -06:00
enabler = ["pytest-enabler (>=2.2)"]
test = ["big-O", "importlib-resources", "jaraco.functools", "jaraco.itertools", "jaraco.test", "more-itertools", "pytest (>=6,!=8.1.*)", "pytest-ignore-flaky"]
type = ["pytest-mypy"]
Making `make install` work better by default. (#2004) # What does this PR do? Making `make install` a much better sane default to start local dev environments. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-06-04 11:38:46 -06:00
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
[extras]
accelerate = ["accelerate"]
bnb = ["bitsandbytes"]
Install Marlin from standalone package (#2320)
2024-07-29 07:37:10 -06:00
marlin = ["marlin-kernels", "marlin-kernels", "marlin-kernels", "marlin-kernels"]
v1.4.1 (#1568)
2024-02-16 09:50:57 -07:00
outlines = ["outlines"]
chore: update to torch 2.1.0 (#1182) Close #1142
2023-11-23 05:38:50 -07:00
peft = ["peft"]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
quantize = ["accelerate", "datasets", "texttable"]
chore: update to torch 2.1.0 (#1182) Close #1142
2023-11-23 05:38:50 -07:00
torch = ["torch"]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 09:22:45 -06:00
[metadata]
lock-version = "2.0"
Merge BNB 4bit. (#770) # What does this PR do? See #626 <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil --> --------- Co-authored-by: krzim <zimmerk4@live.com>
2023-08-03 15:00:59 -06:00
python-versions = ">=3.9,<3.13"
Updating outlines to 0.0.46
2024-09-13 07:38:38 -06:00
content-hash = "3225ea94d09cf65d17703aa6e0b2658c188dd2245ccba93c6cb1e5f0857224af"