feat(server): Add native support for PEFT Lora models (#762)
- Will detect `peft` model by finding `adapter_config.json`.
- This triggers a totally dedicated `download-weights` path
- This path, loads the adapter config, finds the base model_id
- It loads the base_model
- Then peft_model
- Then `merge_and_unload()`
- Then `save_pretrained(.., safe_serialization=True)
- Add back the config + tokenizer.merge_and_unload()`
- Then `save_pretrained(.., safe_serialization=True)
- Add back the config + tokenizer.
- The chosen location is a **local folder with the name of the user
chosen model id**
PROs:
- Easier than to expect user to merge manually
- Barely any change outside of `download-weights` command.
- This means everything will work in a single load.
- Should enable out of the box SM + HFE
CONs:
- Creates a local merged model in unusual location, potentially
not saved across docker reloads, or ovewriting some files if the PEFT
itself was local and containing other files in addition to the lora
Alternatives considered:
- Add `local_files_only=True` every where (discard because of massive
code change for not a good enough reason)
- Return something to `launcher` about the new model-id (a cleaner
location for this new model), but it would
introduce new communication somewhere where we didn't need it before.
- Using the HF cache folder and *stopping* the flow after
`download-weights` and asking user to restart with the actual local
model location
Fix #482
# What does this PR do?
<!--
Congratulations! You've made it this far! You're not quite done yet
though.
Once merged, your PR is going to appear in the release notes with the
title you set, so make sure it's a great title that fully reflects the
extent of your awesome contribution.
Then, please replace this with a description of the change and which
issue is fixed (if applicable). Please also include relevant motivation
and context. List any dependencies (if any) that are required for this
change.
Once you're done, someone will review your PR shortly (see the section
"Who can review?" below to tag some potential reviewers). They may
suggest changes to make the code even better. If no one reviewed your PR
after a week has passed, don't hesitate to post a new comment
@-mentioning the same persons---sometimes notifications get lost.
-->
<!-- Remove if not applicable -->
Fixes # (issue)
## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the
other checks if that's the case).
- [ ] Did you read the [contributor
guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests),
Pull Request section?
- [ ] Was this discussed/approved via a Github issue or the
[forum](https://discuss.huggingface.co/)? Please add a link
to it if that's the case.
- [ ] Did you make sure to update the documentation with your changes?
Here are the
[documentation
guidelines](https://github.com/huggingface/transformers/tree/main/docs),
and
[here are tips on formatting
docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation).
- [ ] Did you write any new necessary tests?
## Who can review?
Anyone in the community is free to review the PR once the tests have
passed. Feel free to tag
members/contributors who may be interested in your PR.
<!-- Your PR will be replied to more quickly if you can figure out the
right person to tag with @
@OlivierDehaene OR @Narsil
-->
2023-08-03 09:22:45 -06:00
|
|
|
# This file is automatically @generated by Poetry 1.5.1 and should not be changed by hand.
|
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"
|
2023-08-11 08:46:08 -06:00
|
|
|
version = "0.20.3"
|
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"
|
2023-07-04 12:23:55 -06:00
|
|
|
optional = false
|
feat(server): Add native support for PEFT Lora models (#762)
- Will detect `peft` model by finding `adapter_config.json`.
- This triggers a totally dedicated `download-weights` path
- This path, loads the adapter config, finds the base model_id
- It loads the base_model
- Then peft_model
- Then `merge_and_unload()`
- Then `save_pretrained(.., safe_serialization=True)
- Add back the config + tokenizer.merge_and_unload()`
- Then `save_pretrained(.., safe_serialization=True)
- Add back the config + tokenizer.
- The chosen location is a **local folder with the name of the user
chosen model id**
PROs:
- Easier than to expect user to merge manually
- Barely any change outside of `download-weights` command.
- This means everything will work in a single load.
- Should enable out of the box SM + HFE
CONs:
- Creates a local merged model in unusual location, potentially
not saved across docker reloads, or ovewriting some files if the PEFT
itself was local and containing other files in addition to the lora
Alternatives considered:
- Add `local_files_only=True` every where (discard because of massive
code change for not a good enough reason)
- Return something to `launcher` about the new model-id (a cleaner
location for this new model), but it would
introduce new communication somewhere where we didn't need it before.
- Using the HF cache folder and *stopping* the flow after
`download-weights` and asking user to restart with the actual local
model location
Fix #482
# What does this PR do?
<!--
Congratulations! You've made it this far! You're not quite done yet
though.
Once merged, your PR is going to appear in the release notes with the
title you set, so make sure it's a great title that fully reflects the
extent of your awesome contribution.
Then, please replace this with a description of the change and which
issue is fixed (if applicable). Please also include relevant motivation
and context. List any dependencies (if any) that are required for this
change.
Once you're done, someone will review your PR shortly (see the section
"Who can review?" below to tag some potential reviewers). They may
suggest changes to make the code even better. If no one reviewed your PR
after a week has passed, don't hesitate to post a new comment
@-mentioning the same persons---sometimes notifications get lost.
-->
<!-- Remove if not applicable -->
Fixes # (issue)
## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the
other checks if that's the case).
- [ ] Did you read the [contributor
guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests),
Pull Request section?
- [ ] Was this discussed/approved via a Github issue or the
[forum](https://discuss.huggingface.co/)? Please add a link
to it if that's the case.
- [ ] Did you make sure to update the documentation with your changes?
Here are the
[documentation
guidelines](https://github.com/huggingface/transformers/tree/main/docs),
and
[here are tips on formatting
docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation).
- [ ] Did you write any new necessary tests?
## Who can review?
Anyone in the community is free to review the PR once the tests have
passed. Feel free to tag
members/contributors who may be interested in your PR.
<!-- Your PR will be replied to 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 = ">=3.7.0"
|
|
|
|
files = [
|
2023-08-11 08:46:08 -06:00
|
|
|
{file = "accelerate-0.20.3-py3-none-any.whl", hash = "sha256:147183e7a2215f7bd45a7af3b986a963daa8a61fa58b0912b9473049e011ad15"},
|
|
|
|
{file = "accelerate-0.20.3.tar.gz", hash = "sha256:79a896978c20dac270083d42bf033f4c9a80dcdd6b946f1ca92d8d6d0f0f5ba9"},
|
feat(server): Add native support for PEFT Lora models (#762)
- Will detect `peft` model by finding `adapter_config.json`.
- This triggers a totally dedicated `download-weights` path
- This path, loads the adapter config, finds the base model_id
- It loads the base_model
- Then peft_model
- Then `merge_and_unload()`
- Then `save_pretrained(.., safe_serialization=True)
- Add back the config + tokenizer.merge_and_unload()`
- Then `save_pretrained(.., safe_serialization=True)
- Add back the config + tokenizer.
- The chosen location is a **local folder with the name of the user
chosen model id**
PROs:
- Easier than to expect user to merge manually
- Barely any change outside of `download-weights` command.
- This means everything will work in a single load.
- Should enable out of the box SM + HFE
CONs:
- Creates a local merged model in unusual location, potentially
not saved across docker reloads, or ovewriting some files if the PEFT
itself was local and containing other files in addition to the lora
Alternatives considered:
- Add `local_files_only=True` every where (discard because of massive
code change for not a good enough reason)
- Return something to `launcher` about the new model-id (a cleaner
location for this new model), but it would
introduce new communication somewhere where we didn't need it before.
- Using the HF cache folder and *stopping* the flow after
`download-weights` and asking user to restart with the actual local
model location
Fix #482
# What does this PR do?
<!--
Congratulations! You've made it this far! You're not quite done yet
though.
Once merged, your PR is going to appear in the release notes with the
title you set, so make sure it's a great title that fully reflects the
extent of your awesome contribution.
Then, please replace this with a description of the change and which
issue is fixed (if applicable). Please also include relevant motivation
and context. List any dependencies (if any) that are required for this
change.
Once you're done, someone will review your PR shortly (see the section
"Who can review?" below to tag some potential reviewers). They may
suggest changes to make the code even better. If no one reviewed your PR
after a week has passed, don't hesitate to post a new comment
@-mentioning the same persons---sometimes notifications get lost.
-->
<!-- Remove if not applicable -->
Fixes # (issue)
## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the
other checks if that's the case).
- [ ] Did you read the [contributor
guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests),
Pull Request section?
- [ ] Was this discussed/approved via a Github issue or the
[forum](https://discuss.huggingface.co/)? Please add a link
to it if that's the case.
- [ ] Did you make sure to update the documentation with your changes?
Here are the
[documentation
guidelines](https://github.com/huggingface/transformers/tree/main/docs),
and
[here are tips on formatting
docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation).
- [ ] Did you write any new necessary tests?
## Who can review?
Anyone in the community is free to review the PR once the tests have
passed. Feel free to tag
members/contributors who may be interested in your PR.
<!-- Your PR will be replied to more quickly if you can figure out the
right person to tag with @
@OlivierDehaene OR @Narsil
-->
2023-08-03 09:22:45 -06:00
|
|
|
]
|
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]
|
|
|
|
numpy = ">=1.17"
|
|
|
|
packaging = ">=20.0"
|
|
|
|
psutil = "*"
|
|
|
|
pyyaml = "*"
|
|
|
|
torch = ">=1.6.0"
|
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 = ["black (>=23.1,<24.0)", "datasets", "deepspeed", "evaluate", "hf-doc-builder (>=0.3.0)", "parameterized", "pytest", "pytest-subtests", "pytest-xdist", "rich", "ruff (>=0.0.241)", "scikit-learn", "scipy", "tqdm", "transformers", "urllib3 (<2.0.0)"]
|
|
|
|
quality = ["black (>=23.1,<24.0)", "hf-doc-builder (>=0.3.0)", "ruff (>=0.0.241)", "urllib3 (<2.0.0)"]
|
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|
rich = ["rich"]
|
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|
sagemaker = ["sagemaker"]
|
|
|
|
test-dev = ["datasets", "deepspeed", "evaluate", "scikit-learn", "scipy", "tqdm", "transformers"]
|
|
|
|
test-prod = ["parameterized", "pytest", "pytest-subtests", "pytest-xdist"]
|
|
|
|
test-trackers = ["comet-ml", "tensorboard", "wandb"]
|
|
|
|
testing = ["datasets", "deepspeed", "evaluate", "parameterized", "pytest", "pytest-subtests", "pytest-xdist", "scikit-learn", "scipy", "tqdm", "transformers"]
|
2023-07-04 12:23:55 -06:00
|
|
|
|
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
|
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name = "aiohttp"
|
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version = "3.8.5"
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description = "Async http client/server framework (asyncio)"
|
2023-07-27 06:50:45 -06:00
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optional = true
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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
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{file = "aiohttp-3.8.5-cp38-cp38-win32.whl", hash = "sha256:ab88bafedc57dd0aab55fa728ea10c1911f7e4d8b43e1d838a1739f33712921c"},
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{file = "aiohttp-3.8.5-cp38-cp38-win_amd64.whl", hash = "sha256:5798a9aad1879f626589f3df0f8b79b3608a92e9beab10e5fda02c8a2c60db2e"},
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{file = "aiohttp-3.8.5-cp39-cp39-macosx_10_9_universal2.whl", hash = "sha256:a6ce61195c6a19c785df04e71a4537e29eaa2c50fe745b732aa937c0c77169f3"},
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{file = "aiohttp-3.8.5-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:773dd01706d4db536335fcfae6ea2440a70ceb03dd3e7378f3e815b03c97ab51"},
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{file = "aiohttp-3.8.5-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:f83a552443a526ea38d064588613aca983d0ee0038801bc93c0c916428310c28"},
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{file = "aiohttp-3.8.5-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:e5d47ae48db0b2dcf70bc8a3bc72b3de86e2a590fc299fdbbb15af320d2659de"},
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{file = "aiohttp-3.8.5-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:d827176898a2b0b09694fbd1088c7a31836d1a505c243811c87ae53a3f6273c1"},
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{file = "aiohttp-3.8.5-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:3562b06567c06439d8b447037bb655ef69786c590b1de86c7ab81efe1c9c15d8"},
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{file = "aiohttp-3.8.5-cp39-cp39-musllinux_1_1_aarch64.whl", hash = "sha256:4e874cbf8caf8959d2adf572a78bba17cb0e9d7e51bb83d86a3697b686a0ab4d"},
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{file = "aiohttp-3.8.5-cp39-cp39-musllinux_1_1_i686.whl", hash = "sha256:6809a00deaf3810e38c628e9a33271892f815b853605a936e2e9e5129762356c"},
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{file = "aiohttp-3.8.5-cp39-cp39-musllinux_1_1_ppc64le.whl", hash = "sha256:33776e945d89b29251b33a7e7d006ce86447b2cfd66db5e5ded4e5cd0340585c"},
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{file = "aiohttp-3.8.5-cp39-cp39-musllinux_1_1_s390x.whl", hash = "sha256:eaeed7abfb5d64c539e2db173f63631455f1196c37d9d8d873fc316470dfbacd"},
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{file = "aiohttp-3.8.5-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:e91d635961bec2d8f19dfeb41a539eb94bd073f075ca6dae6c8dc0ee89ad6f91"},
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{file = "aiohttp-3.8.5-cp39-cp39-win32.whl", hash = "sha256:00ad4b6f185ec67f3e6562e8a1d2b69660be43070bd0ef6fcec5211154c7df67"},
|
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{file = "aiohttp-3.8.5-cp39-cp39-win_amd64.whl", hash = "sha256:c0a9034379a37ae42dea7ac1e048352d96286626251862e448933c0f59cbd79c"},
|
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|
{file = "aiohttp-3.8.5.tar.gz", hash = "sha256:b9552ec52cc147dbf1944ac7ac98af7602e51ea2dcd076ed194ca3c0d1c7d0bc"},
|
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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
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[package.dependencies]
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aiosignal = ">=1.1.2"
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async-timeout = ">=4.0.0a3,<5.0"
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attrs = ">=17.3.0"
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charset-normalizer = ">=2.0,<4.0"
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frozenlist = ">=1.1.1"
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multidict = ">=4.5,<7.0"
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yarl = ">=1.0,<2.0"
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[package.extras]
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speedups = ["Brotli", "aiodns", "cchardet"]
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[[package]]
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name = "aiosignal"
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|
version = "1.3.1"
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|
description = "aiosignal: a list of registered asynchronous callbacks"
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optional = true
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|
|
python-versions = ">=3.7"
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|
files = [
|
2023-07-27 06:50:45 -06:00
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|
{file = "aiosignal-1.3.1-py3-none-any.whl", hash = "sha256:f8376fb07dd1e86a584e4fcdec80b36b7f81aac666ebc724e2c090300dd83b17"},
|
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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
|
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|
|
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|
|
[package.dependencies]
|
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|
frozenlist = ">=1.1.0"
|
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[[package]]
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name = "async-timeout"
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2023-08-17 06:38:49 -06:00
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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"
|
|
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|
optional = true
|
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 = [
|
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"},
|
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
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[[package]]
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name = "attrs"
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version = "23.1.0"
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description = "Classes Without Boilerplate"
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optional = true
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python-versions = ">=3.7"
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files = [
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2023-07-27 06:50:45 -06:00
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{file = "attrs-23.1.0-py3-none-any.whl", hash = "sha256:1f28b4522cdc2fb4256ac1a020c78acf9cba2c6b461ccd2c126f3aa8e8335d04"},
|
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|
{file = "attrs-23.1.0.tar.gz", hash = "sha256:6279836d581513a26f1bf235f9acd333bc9115683f14f7e8fae46c98fc50e015"},
|
|
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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
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[package.extras]
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cov = ["attrs[tests]", "coverage[toml] (>=5.3)"]
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dev = ["attrs[docs,tests]", "pre-commit"]
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docs = ["furo", "myst-parser", "sphinx", "sphinx-notfound-page", "sphinxcontrib-towncrier", "towncrier", "zope-interface"]
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tests = ["attrs[tests-no-zope]", "zope-interface"]
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|
tests-no-zope = ["cloudpickle", "hypothesis", "mypy (>=1.1.1)", "pympler", "pytest (>=4.3.0)", "pytest-mypy-plugins", "pytest-xdist[psutil]"]
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[[package]]
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|
|
name = "backoff"
|
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|
version = "2.2.1"
|
|
|
|
description = "Function decoration for backoff and retry"
|
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optional = false
|
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|
python-versions = ">=3.7,<4.0"
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files = [
|
2023-07-04 12:23:55 -06:00
|
|
|
{file = "backoff-2.2.1-py3-none-any.whl", hash = "sha256:63579f9a0628e06278f7e47b7d7d5b6ce20dc65c5e96a6f3ca99a6adca0396e8"},
|
|
|
|
{file = "backoff-2.2.1.tar.gz", hash = "sha256:03f829f5bb1923180821643f8753b0502c3b682293992485b0eef2807afa5cba"},
|
|
|
|
]
|
feat(server): Add native support for PEFT Lora models (#762)
- Will detect `peft` model by finding `adapter_config.json`.
- This triggers a totally dedicated `download-weights` path
- This path, loads the adapter config, finds the base model_id
- It loads the base_model
- Then peft_model
- Then `merge_and_unload()`
- Then `save_pretrained(.., safe_serialization=True)
- Add back the config + tokenizer.merge_and_unload()`
- Then `save_pretrained(.., safe_serialization=True)
- Add back the config + tokenizer.
- The chosen location is a **local folder with the name of the user
chosen model id**
PROs:
- Easier than to expect user to merge manually
- Barely any change outside of `download-weights` command.
- This means everything will work in a single load.
- Should enable out of the box SM + HFE
CONs:
- Creates a local merged model in unusual location, potentially
not saved across docker reloads, or ovewriting some files if the PEFT
itself was local and containing other files in addition to the lora
Alternatives considered:
- Add `local_files_only=True` every where (discard because of massive
code change for not a good enough reason)
- Return something to `launcher` about the new model-id (a cleaner
location for this new model), but it would
introduce new communication somewhere where we didn't need it before.
- Using the HF cache folder and *stopping* the flow after
`download-weights` and asking user to restart with the actual local
model location
Fix #482
# What does this PR do?
<!--
Congratulations! You've made it this far! You're not quite done yet
though.
Once merged, your PR is going to appear in the release notes with the
title you set, so make sure it's a great title that fully reflects the
extent of your awesome contribution.
Then, please replace this with a description of the change and which
issue is fixed (if applicable). Please also include relevant motivation
and context. List any dependencies (if any) that are required for this
change.
Once you're done, someone will review your PR shortly (see the section
"Who can review?" below to tag some potential reviewers). They may
suggest changes to make the code even better. If no one reviewed your PR
after a week has passed, don't hesitate to post a new comment
@-mentioning the same persons---sometimes notifications get lost.
-->
<!-- Remove if not applicable -->
Fixes # (issue)
## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the
other checks if that's the case).
- [ ] Did you read the [contributor
guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests),
Pull Request section?
- [ ] Was this discussed/approved via a Github issue or the
[forum](https://discuss.huggingface.co/)? Please add a link
to it if that's the case.
- [ ] Did you make sure to update the documentation with your changes?
Here are the
[documentation
guidelines](https://github.com/huggingface/transformers/tree/main/docs),
and
[here are tips on formatting
docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation).
- [ ] Did you write any new necessary tests?
## Who can review?
Anyone in the community is free to review the PR once the tests have
passed. Feel free to tag
members/contributors who may be interested in your PR.
<!-- Your PR will be replied to 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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|
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|
|
[[package]]
|
|
|
|
name = "bitsandbytes"
|
2023-08-11 08:46:08 -06:00
|
|
|
version = "0.41.1"
|
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 = [
|
2023-08-11 08:46:08 -06:00
|
|
|
{file = "bitsandbytes-0.41.1-py3-none-any.whl", hash = "sha256:b25228c27636367f222232ed4d1e1502eedd2064be215633734fb8ea0c1c65f4"},
|
|
|
|
{file = "bitsandbytes-0.41.1.tar.gz", hash = "sha256:b3f8e7e1e5f88d4813d10ebd4072034ba6a18eca7f0e255376f8320e5499032c"},
|
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 = "certifi"
|
2023-08-03 13:54:39 -06:00
|
|
|
version = "2023.7.22"
|
feat(server): Add native support for PEFT Lora models (#762)
- Will detect `peft` model by finding `adapter_config.json`.
- This triggers a totally dedicated `download-weights` path
- This path, loads the adapter config, finds the base model_id
- It loads the base_model
- Then peft_model
- Then `merge_and_unload()`
- Then `save_pretrained(.., safe_serialization=True)
- Add back the config + tokenizer.merge_and_unload()`
- Then `save_pretrained(.., safe_serialization=True)
- Add back the config + tokenizer.
- The chosen location is a **local folder with the name of the user
chosen model id**
PROs:
- Easier than to expect user to merge manually
- Barely any change outside of `download-weights` command.
- This means everything will work in a single load.
- Should enable out of the box SM + HFE
CONs:
- Creates a local merged model in unusual location, potentially
not saved across docker reloads, or ovewriting some files if the PEFT
itself was local and containing other files in addition to the lora
Alternatives considered:
- Add `local_files_only=True` every where (discard because of massive
code change for not a good enough reason)
- Return something to `launcher` about the new model-id (a cleaner
location for this new model), but it would
introduce new communication somewhere where we didn't need it before.
- Using the HF cache folder and *stopping* the flow after
`download-weights` and asking user to restart with the actual local
model location
Fix #482
# What does this PR do?
<!--
Congratulations! You've made it this far! You're not quite done yet
though.
Once merged, your PR is going to appear in the release notes with the
title you set, so make sure it's a great title that fully reflects the
extent of your awesome contribution.
Then, please replace this with a description of the change and which
issue is fixed (if applicable). Please also include relevant motivation
and context. List any dependencies (if any) that are required for this
change.
Once you're done, someone will review your PR shortly (see the section
"Who can review?" below to tag some potential reviewers). They may
suggest changes to make the code even better. If no one reviewed your PR
after a week has passed, don't hesitate to post a new comment
@-mentioning the same persons---sometimes notifications get lost.
-->
<!-- Remove if not applicable -->
Fixes # (issue)
## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the
other checks if that's the case).
- [ ] Did you read the [contributor
guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests),
Pull Request section?
- [ ] Was this discussed/approved via a Github issue or the
[forum](https://discuss.huggingface.co/)? Please add a link
to it if that's the case.
- [ ] Did you make sure to update the documentation with your changes?
Here are the
[documentation
guidelines](https://github.com/huggingface/transformers/tree/main/docs),
and
[here are tips on formatting
docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation).
- [ ] Did you write any new necessary tests?
## Who can review?
Anyone in the community is free to review the PR once the tests have
passed. Feel free to tag
members/contributors who may be interested in your PR.
<!-- Your PR will be replied to 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 = [
|
2023-08-03 13:54:39 -06:00
|
|
|
{file = "certifi-2023.7.22-py3-none-any.whl", hash = "sha256:92d6037539857d8206b8f6ae472e8b77db8058fec5937a1ef3f54304089edbb9"},
|
|
|
|
{file = "certifi-2023.7.22.tar.gz", hash = "sha256:539cc1d13202e33ca466e88b2807e29f4c13049d6d87031a3c110744495cb082"},
|
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
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[[package]]
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name = "charset-normalizer"
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2023-08-03 13:54:39 -06:00
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version = "3.2.0"
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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?
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Fixes # (issue)
## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the
other checks if that's the case).
- [ ] Did you read the [contributor
guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests),
Pull Request section?
- [ ] Was this discussed/approved via a Github issue or the
[forum](https://discuss.huggingface.co/)? Please add a link
to it if that's the case.
- [ ] Did you make sure to update the documentation with your changes?
Here are the
[documentation
guidelines](https://github.com/huggingface/transformers/tree/main/docs),
and
[here are tips on formatting
docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation).
- [ ] Did you write any new necessary tests?
## Who can review?
Anyone in the community is free to review the PR once the tests have
passed. Feel free to tag
members/contributors who may be interested in your PR.
<!-- Your PR will be replied to 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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description = "The Real First Universal Charset Detector. Open, modern and actively maintained alternative to Chardet."
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optional = false
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python-versions = ">=3.7.0"
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2023-08-03 13:54:39 -06:00
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{file = "charset_normalizer-3.2.0-cp39-cp39-musllinux_1_1_i686.whl", hash = "sha256:f7560358a6811e52e9c4d142d497f1a6e10103d3a6881f18d04dbce3729c0e2c"},
|
|
|
|
{file = "charset_normalizer-3.2.0-cp39-cp39-musllinux_1_1_ppc64le.whl", hash = "sha256:c8063cf17b19661471ecbdb3df1c84f24ad2e389e326ccaf89e3fb2484d8dd7e"},
|
|
|
|
{file = "charset_normalizer-3.2.0-cp39-cp39-musllinux_1_1_s390x.whl", hash = "sha256:cd6dbe0238f7743d0efe563ab46294f54f9bc8f4b9bcf57c3c666cc5bc9d1299"},
|
|
|
|
{file = "charset_normalizer-3.2.0-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:1249cbbf3d3b04902ff081ffbb33ce3377fa6e4c7356f759f3cd076cc138d020"},
|
|
|
|
{file = "charset_normalizer-3.2.0-cp39-cp39-win32.whl", hash = "sha256:6c409c0deba34f147f77efaa67b8e4bb83d2f11c8806405f76397ae5b8c0d1c9"},
|
|
|
|
{file = "charset_normalizer-3.2.0-cp39-cp39-win_amd64.whl", hash = "sha256:7095f6fbfaa55defb6b733cfeb14efaae7a29f0b59d8cf213be4e7ca0b857b80"},
|
|
|
|
{file = "charset_normalizer-3.2.0-py3-none-any.whl", hash = "sha256:8e098148dd37b4ce3baca71fb394c81dc5d9c7728c95df695d2dca218edf40e6"},
|
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"
|
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 = [
|
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"},
|
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\""}
|
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|
|
|
|
|
|
[[package]]
|
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|
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 = [
|
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"
|
2023-08-17 06:38:49 -06:00
|
|
|
version = "2.14.4"
|
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 = "HuggingFace community-driven open-source library of datasets"
|
|
|
|
optional = true
|
|
|
|
python-versions = ">=3.8.0"
|
|
|
|
files = [
|
2023-08-17 06:38:49 -06:00
|
|
|
{file = "datasets-2.14.4-py3-none-any.whl", hash = "sha256:29336bd316a7d827ccd4da2236596279b20ca2ac78f64c04c9483da7cbc2459b"},
|
|
|
|
{file = "datasets-2.14.4.tar.gz", hash = "sha256:ef29c2b5841de488cd343cfc26ab979bff77efa4d2285af51f1ad7db5c46a83b"},
|
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 = "*"
|
|
|
|
dill = ">=0.3.0,<0.3.8"
|
|
|
|
fsspec = {version = ">=2021.11.1", extras = ["http"]}
|
|
|
|
huggingface-hub = ">=0.14.0,<1.0.0"
|
|
|
|
multiprocess = "*"
|
|
|
|
numpy = ">=1.17"
|
|
|
|
packaging = "*"
|
|
|
|
pandas = "*"
|
|
|
|
pyarrow = ">=8.0.0"
|
|
|
|
pyyaml = ">=5.1"
|
|
|
|
requests = ">=2.19.0"
|
|
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|
tqdm = ">=4.62.1"
|
|
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xxhash = "*"
|
|
|
|
|
|
|
|
[package.extras]
|
|
|
|
apache-beam = ["apache-beam (>=2.26.0,<2.44.0)"]
|
|
|
|
audio = ["librosa", "soundfile (>=0.12.1)"]
|
|
|
|
benchmarks = ["tensorflow (==2.12.0)", "torch (==2.0.1)", "transformers (==4.30.1)"]
|
2023-08-03 13:54:39 -06:00
|
|
|
dev = ["Pillow (>=6.2.1)", "absl-py", "apache-beam (>=2.26.0,<2.44.0)", "black (>=23.1,<24.0)", "elasticsearch (<8.0.0)", "faiss-cpu (>=1.6.4)", "joblib (<1.3.0)", "joblibspark", "librosa", "lz4", "py7zr", "pyspark (>=3.4)", "pytest", "pytest-datadir", "pytest-xdist", "pyyaml (>=5.3.1)", "rarfile (>=4.0)", "ruff (>=0.0.241)", "s3fs", "s3fs (>=2021.11.1)", "soundfile (>=0.12.1)", "sqlalchemy (<2.0.0)", "tensorflow (>=2.2.0,!=2.6.0,!=2.6.1)", "tensorflow (>=2.3,!=2.6.0,!=2.6.1)", "tensorflow-macos", "tiktoken", "torch", "transformers", "zstandard"]
|
|
|
|
docs = ["s3fs", "tensorflow (>=2.2.0,!=2.6.0,!=2.6.1)", "tensorflow-macos", "torch", "transformers"]
|
feat(server): Add native support for PEFT Lora models (#762)
- Will detect `peft` model by finding `adapter_config.json`.
- This triggers a totally dedicated `download-weights` path
- This path, loads the adapter config, finds the base model_id
- It loads the base_model
- Then peft_model
- Then `merge_and_unload()`
- Then `save_pretrained(.., safe_serialization=True)
- Add back the config + tokenizer.merge_and_unload()`
- Then `save_pretrained(.., safe_serialization=True)
- Add back the config + tokenizer.
- The chosen location is a **local folder with the name of the user
chosen model id**
PROs:
- Easier than to expect user to merge manually
- Barely any change outside of `download-weights` command.
- This means everything will work in a single load.
- Should enable out of the box SM + HFE
CONs:
- Creates a local merged model in unusual location, potentially
not saved across docker reloads, or ovewriting some files if the PEFT
itself was local and containing other files in addition to the lora
Alternatives considered:
- Add `local_files_only=True` every where (discard because of massive
code change for not a good enough reason)
- Return something to `launcher` about the new model-id (a cleaner
location for this new model), but it would
introduce new communication somewhere where we didn't need it before.
- Using the HF cache folder and *stopping* the flow after
`download-weights` and asking user to restart with the actual local
model location
Fix #482
# What does this PR do?
<!--
Congratulations! You've made it this far! You're not quite done yet
though.
Once merged, your PR is going to appear in the release notes with the
title you set, so make sure it's a great title that fully reflects the
extent of your awesome contribution.
Then, please replace this with a description of the change and which
issue is fixed (if applicable). Please also include relevant motivation
and context. List any dependencies (if any) that are required for this
change.
Once you're done, someone will review your PR shortly (see the section
"Who can review?" below to tag some potential reviewers). They may
suggest changes to make the code even better. If no one reviewed your PR
after a week has passed, don't hesitate to post a new comment
@-mentioning the same persons---sometimes notifications get lost.
-->
<!-- Remove if not applicable -->
Fixes # (issue)
## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the
other checks if that's the case).
- [ ] Did you read the [contributor
guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests),
Pull Request section?
- [ ] Was this discussed/approved via a Github issue or the
[forum](https://discuss.huggingface.co/)? Please add a link
to it if that's the case.
- [ ] Did you make sure to update the documentation with your changes?
Here are the
[documentation
guidelines](https://github.com/huggingface/transformers/tree/main/docs),
and
[here are tips on formatting
docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation).
- [ ] Did you write any new necessary tests?
## Who can review?
Anyone in the community is free to review the PR once the tests have
passed. Feel free to tag
members/contributors who may be interested in your PR.
<!-- Your PR will be replied to more quickly if you can figure out the
right person to tag with @
@OlivierDehaene OR @Narsil
-->
2023-08-03 09:22:45 -06:00
|
|
|
jax = ["jax (>=0.2.8,!=0.3.2,<=0.3.25)", "jaxlib (>=0.1.65,<=0.3.25)"]
|
|
|
|
metrics-tests = ["Werkzeug (>=1.0.1)", "accelerate", "bert-score (>=0.3.6)", "jiwer", "langdetect", "mauve-text", "nltk", "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)"]
|
|
|
|
quality = ["black (>=23.1,<24.0)", "pyyaml (>=5.3.1)", "ruff (>=0.0.241)"]
|
|
|
|
s3 = ["s3fs"]
|
|
|
|
tensorflow = ["tensorflow (>=2.2.0,!=2.6.0,!=2.6.1)", "tensorflow-macos"]
|
|
|
|
tensorflow-gpu = ["tensorflow-gpu (>=2.2.0,!=2.6.0,!=2.6.1)"]
|
|
|
|
tests = ["Pillow (>=6.2.1)", "absl-py", "apache-beam (>=2.26.0,<2.44.0)", "elasticsearch (<8.0.0)", "faiss-cpu (>=1.6.4)", "joblib (<1.3.0)", "joblibspark", "librosa", "lz4", "py7zr", "pyspark (>=3.4)", "pytest", "pytest-datadir", "pytest-xdist", "rarfile (>=4.0)", "s3fs (>=2021.11.1)", "soundfile (>=0.12.1)", "sqlalchemy (<2.0.0)", "tensorflow (>=2.3,!=2.6.0,!=2.6.1)", "tensorflow-macos", "tiktoken", "torch", "transformers", "zstandard"]
|
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|
|
torch = ["torch"]
|
|
|
|
vision = ["Pillow (>=6.2.1)"]
|
|
|
|
|
|
|
|
[[package]]
|
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."
|
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|
|
optional = false
|
|
|
|
python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
|
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|
|
files = [
|
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]
|
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|
wrapt = ">=1.10,<2"
|
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|
|
[package.extras]
|
|
|
|
dev = ["PyTest", "PyTest-Cov", "bump2version (<1)", "sphinx (<2)", "tox"]
|
|
|
|
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[[package]]
|
|
|
|
name = "dill"
|
|
|
|
version = "0.3.7"
|
|
|
|
description = "serialize all of Python"
|
|
|
|
optional = true
|
|
|
|
python-versions = ">=3.7"
|
|
|
|
files = [
|
2023-07-27 06:50:45 -06:00
|
|
|
{file = "dill-0.3.7-py3-none-any.whl", hash = "sha256:76b122c08ef4ce2eedcd4d1abd8e641114bfc6c2867f49f3c41facf65bf19f5e"},
|
|
|
|
{file = "dill-0.3.7.tar.gz", hash = "sha256:cc1c8b182eb3013e24bd475ff2e9295af86c1a38eb1aff128dac8962a9ce3c03"},
|
|
|
|
]
|
feat(server): Add native support for PEFT Lora models (#762)
- Will detect `peft` model by finding `adapter_config.json`.
- This triggers a totally dedicated `download-weights` path
- This path, loads the adapter config, finds the base model_id
- It loads the base_model
- Then peft_model
- Then `merge_and_unload()`
- Then `save_pretrained(.., safe_serialization=True)
- Add back the config + tokenizer.merge_and_unload()`
- Then `save_pretrained(.., safe_serialization=True)
- Add back the config + tokenizer.
- The chosen location is a **local folder with the name of the user
chosen model id**
PROs:
- Easier than to expect user to merge manually
- Barely any change outside of `download-weights` command.
- This means everything will work in a single load.
- Should enable out of the box SM + HFE
CONs:
- Creates a local merged model in unusual location, potentially
not saved across docker reloads, or ovewriting some files if the PEFT
itself was local and containing other files in addition to the lora
Alternatives considered:
- Add `local_files_only=True` every where (discard because of massive
code change for not a good enough reason)
- Return something to `launcher` about the new model-id (a cleaner
location for this new model), but it would
introduce new communication somewhere where we didn't need it before.
- Using the HF cache folder and *stopping* the flow after
`download-weights` and asking user to restart with the actual local
model location
Fix #482
# What does this PR do?
<!--
Congratulations! You've made it this far! You're not quite done yet
though.
Once merged, your PR is going to appear in the release notes with the
title you set, so make sure it's a great title that fully reflects the
extent of your awesome contribution.
Then, please replace this with a description of the change and which
issue is fixed (if applicable). Please also include relevant motivation
and context. List any dependencies (if any) that are required for this
change.
Once you're done, someone will review your PR shortly (see the section
"Who can review?" below to tag some potential reviewers). They may
suggest changes to make the code even better. If no one reviewed your PR
after a week has passed, don't hesitate to post a new comment
@-mentioning the same persons---sometimes notifications get lost.
-->
<!-- Remove if not applicable -->
Fixes # (issue)
## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the
other checks if that's the case).
- [ ] Did you read the [contributor
guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests),
Pull Request section?
- [ ] Was this discussed/approved via a Github issue or the
[forum](https://discuss.huggingface.co/)? Please add a link
to it if that's the case.
- [ ] Did you make sure to update the documentation with your changes?
Here are the
[documentation
guidelines](https://github.com/huggingface/transformers/tree/main/docs),
and
[here are tips on formatting
docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation).
- [ ] Did you write any new necessary tests?
## Who can review?
Anyone in the community is free to review the PR once the tests have
passed. Feel free to tag
members/contributors who may be interested in your PR.
<!-- Your PR will be replied to 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)"]
|
|
|
|
|
|
|
|
[[package]]
|
|
|
|
name = "einops"
|
|
|
|
version = "0.6.1"
|
|
|
|
description = "A new flavour of deep learning operations"
|
|
|
|
optional = false
|
|
|
|
python-versions = ">=3.7"
|
|
|
|
files = [
|
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"
|
2023-08-17 06:38:49 -06:00
|
|
|
version = "1.1.3"
|
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 = "Backport of PEP 654 (exception groups)"
|
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optional = false
|
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|
|
python-versions = ">=3.7"
|
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|
|
files = [
|
2023-08-17 06:38:49 -06:00
|
|
|
{file = "exceptiongroup-1.1.3-py3-none-any.whl", hash = "sha256:343280667a4585d195ca1cf9cef84a4e178c4b6cf2274caef9859782b567d5e3"},
|
|
|
|
{file = "exceptiongroup-1.1.3.tar.gz", hash = "sha256:097acd85d473d75af5bb98e41b61ff7fe35efe6675e4f9370ec6ec5126d160e9"},
|
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)"]
|
|
|
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|
|
|
|
[[package]]
|
|
|
|
name = "filelock"
|
2023-08-29 06:28:22 -06:00
|
|
|
version = "3.12.3"
|
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 = "A platform independent file lock."
|
|
|
|
optional = false
|
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 = [
|
2023-08-29 06:28:22 -06:00
|
|
|
{file = "filelock-3.12.3-py3-none-any.whl", hash = "sha256:f067e40ccc40f2b48395a80fcbd4728262fab54e232e090a4063ab804179efeb"},
|
|
|
|
{file = "filelock-3.12.3.tar.gz", hash = "sha256:0ecc1dd2ec4672a10c8550a8182f1bd0c0a5088470ecd5a125e45f49472fac3d"},
|
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
|
|
|
|
2023-08-29 06:28:22 -06:00
|
|
|
[package.dependencies]
|
|
|
|
typing-extensions = {version = ">=4.7.1", 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.extras]
|
2023-08-29 06:28:22 -06:00
|
|
|
docs = ["furo (>=2023.7.26)", "sphinx (>=7.1.2)", "sphinx-autodoc-typehints (>=1.24)"]
|
|
|
|
testing = ["covdefaults (>=2.3)", "coverage (>=7.3)", "diff-cover (>=7.7)", "pytest (>=7.4)", "pytest-cov (>=4.1)", "pytest-mock (>=3.11.1)", "pytest-timeout (>=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 = "frozenlist"
|
|
|
|
version = "1.4.0"
|
|
|
|
description = "A list-like structure which implements collections.abc.MutableSequence"
|
|
|
|
optional = true
|
|
|
|
python-versions = ">=3.8"
|
|
|
|
files = [
|
2023-07-27 06:50:45 -06:00
|
|
|
{file = "frozenlist-1.4.0-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:764226ceef3125e53ea2cb275000e309c0aa5464d43bd72abd661e27fffc26ab"},
|
|
|
|
{file = "frozenlist-1.4.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:d6484756b12f40003c6128bfcc3fa9f0d49a687e171186c2d85ec82e3758c559"},
|
|
|
|
{file = "frozenlist-1.4.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:9ac08e601308e41eb533f232dbf6b7e4cea762f9f84f6357136eed926c15d12c"},
|
|
|
|
{file = "frozenlist-1.4.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:d081f13b095d74b67d550de04df1c756831f3b83dc9881c38985834387487f1b"},
|
|
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{file = "frozenlist-1.4.0.tar.gz", hash = "sha256:09163bdf0b2907454042edb19f887c6d33806adc71fbd54afc14908bfdc22251"},
|
|
|
|
]
|
feat(server): Add native support for PEFT Lora models (#762)
- Will detect `peft` model by finding `adapter_config.json`.
- This triggers a totally dedicated `download-weights` path
- This path, loads the adapter config, finds the base model_id
- It loads the base_model
- Then peft_model
- Then `merge_and_unload()`
- Then `save_pretrained(.., safe_serialization=True)
- Add back the config + tokenizer.merge_and_unload()`
- Then `save_pretrained(.., safe_serialization=True)
- Add back the config + tokenizer.
- The chosen location is a **local folder with the name of the user
chosen model id**
PROs:
- Easier than to expect user to merge manually
- Barely any change outside of `download-weights` command.
- This means everything will work in a single load.
- Should enable out of the box SM + HFE
CONs:
- Creates a local merged model in unusual location, potentially
not saved across docker reloads, or ovewriting some files if the PEFT
itself was local and containing other files in addition to the lora
Alternatives considered:
- Add `local_files_only=True` every where (discard because of massive
code change for not a good enough reason)
- Return something to `launcher` about the new model-id (a cleaner
location for this new model), but it would
introduce new communication somewhere where we didn't need it before.
- Using the HF cache folder and *stopping* the flow after
`download-weights` and asking user to restart with the actual local
model location
Fix #482
# What does this PR do?
<!--
Congratulations! You've made it this far! You're not quite done yet
though.
Once merged, your PR is going to appear in the release notes with the
title you set, so make sure it's a great title that fully reflects the
extent of your awesome contribution.
Then, please replace this with a description of the change and which
issue is fixed (if applicable). Please also include relevant motivation
and context. List any dependencies (if any) that are required for this
change.
Once you're done, someone will review your PR shortly (see the section
"Who can review?" below to tag some potential reviewers). They may
suggest changes to make the code even better. If no one reviewed your PR
after a week has passed, don't hesitate to post a new comment
@-mentioning the same persons---sometimes notifications get lost.
-->
<!-- Remove if not applicable -->
Fixes # (issue)
## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the
other checks if that's the case).
- [ ] Did you read the [contributor
guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests),
Pull Request section?
- [ ] Was this discussed/approved via a Github issue or the
[forum](https://discuss.huggingface.co/)? Please add a link
to it if that's the case.
- [ ] Did you make sure to update the documentation with your changes?
Here are the
[documentation
guidelines](https://github.com/huggingface/transformers/tree/main/docs),
and
[here are tips on formatting
docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation).
- [ ] Did you write any new necessary tests?
## Who can review?
Anyone in the community is free to review the PR once the tests have
passed. Feel free to tag
members/contributors who may be interested in your PR.
<!-- Your PR will be replied to 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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|
[[package]]
|
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|
name = "fsspec"
|
|
|
|
version = "2023.6.0"
|
|
|
|
description = "File-system specification"
|
|
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|
optional = false
|
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|
python-versions = ">=3.8"
|
|
|
|
files = [
|
2023-07-04 12:23:55 -06:00
|
|
|
{file = "fsspec-2023.6.0-py3-none-any.whl", hash = "sha256:1cbad1faef3e391fba6dc005ae9b5bdcbf43005c9167ce78c915549c352c869a"},
|
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|
{file = "fsspec-2023.6.0.tar.gz", hash = "sha256:d0b2f935446169753e7a5c5c55681c54ea91996cc67be93c39a154fb3a2742af"},
|
|
|
|
]
|
feat(server): Add native support for PEFT Lora models (#762)
- Will detect `peft` model by finding `adapter_config.json`.
- This triggers a totally dedicated `download-weights` path
- This path, loads the adapter config, finds the base model_id
- It loads the base_model
- Then peft_model
- Then `merge_and_unload()`
- Then `save_pretrained(.., safe_serialization=True)
- Add back the config + tokenizer.merge_and_unload()`
- Then `save_pretrained(.., safe_serialization=True)
- Add back the config + tokenizer.
- The chosen location is a **local folder with the name of the user
chosen model id**
PROs:
- Easier than to expect user to merge manually
- Barely any change outside of `download-weights` command.
- This means everything will work in a single load.
- Should enable out of the box SM + HFE
CONs:
- Creates a local merged model in unusual location, potentially
not saved across docker reloads, or ovewriting some files if the PEFT
itself was local and containing other files in addition to the lora
Alternatives considered:
- Add `local_files_only=True` every where (discard because of massive
code change for not a good enough reason)
- Return something to `launcher` about the new model-id (a cleaner
location for this new model), but it would
introduce new communication somewhere where we didn't need it before.
- Using the HF cache folder and *stopping* the flow after
`download-weights` and asking user to restart with the actual local
model location
Fix #482
# What does this PR do?
<!--
Congratulations! You've made it this far! You're not quite done yet
though.
Once merged, your PR is going to appear in the release notes with the
title you set, so make sure it's a great title that fully reflects the
extent of your awesome contribution.
Then, please replace this with a description of the change and which
issue is fixed (if applicable). Please also include relevant motivation
and context. List any dependencies (if any) that are required for this
change.
Once you're done, someone will review your PR shortly (see the section
"Who can review?" below to tag some potential reviewers). They may
suggest changes to make the code even better. If no one reviewed your PR
after a week has passed, don't hesitate to post a new comment
@-mentioning the same persons---sometimes notifications get lost.
-->
<!-- Remove if not applicable -->
Fixes # (issue)
## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the
other checks if that's the case).
- [ ] Did you read the [contributor
guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests),
Pull Request section?
- [ ] Was this discussed/approved via a Github issue or the
[forum](https://discuss.huggingface.co/)? Please add a link
to it if that's the case.
- [ ] Did you make sure to update the documentation with your changes?
Here are the
[documentation
guidelines](https://github.com/huggingface/transformers/tree/main/docs),
and
[here are tips on formatting
docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation).
- [ ] Did you write any new necessary tests?
## Who can review?
Anyone in the community is free to review the PR once the tests have
passed. Feel free to tag
members/contributors who may be interested in your PR.
<!-- Your PR will be replied to 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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|
[package.dependencies]
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aiohttp = {version = "<4.0.0a0 || >4.0.0a0,<4.0.0a1 || >4.0.0a1", optional = true, markers = "extra == \"http\""}
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requests = {version = "*", optional = true, markers = "extra == \"http\""}
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[package.extras]
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|
abfs = ["adlfs"]
|
|
|
|
adl = ["adlfs"]
|
|
|
|
arrow = ["pyarrow (>=1)"]
|
|
|
|
dask = ["dask", "distributed"]
|
|
|
|
devel = ["pytest", "pytest-cov"]
|
|
|
|
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)"]
|
|
|
|
http = ["aiohttp (!=4.0.0a0,!=4.0.0a1)", "requests"]
|
|
|
|
libarchive = ["libarchive-c"]
|
|
|
|
oci = ["ocifs"]
|
|
|
|
s3 = ["s3fs"]
|
|
|
|
sftp = ["paramiko"]
|
|
|
|
smb = ["smbprotocol"]
|
|
|
|
ssh = ["paramiko"]
|
|
|
|
tqdm = ["tqdm"]
|
|
|
|
|
|
|
|
[[package]]
|
|
|
|
name = "googleapis-common-protos"
|
2023-08-03 13:54:39 -06:00
|
|
|
version = "1.60.0"
|
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 = [
|
2023-08-03 13:54:39 -06:00
|
|
|
{file = "googleapis-common-protos-1.60.0.tar.gz", hash = "sha256:e73ebb404098db405ba95d1e1ae0aa91c3e15a71da031a2eeb6b2e23e7bc3708"},
|
|
|
|
{file = "googleapis_common_protos-1.60.0-py2.py3-none-any.whl", hash = "sha256:69f9bbcc6acde92cab2db95ce30a70bd2b81d20b12eff3f1aabaffcbe8a93918"},
|
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,<3.20.0 || >3.20.0,<3.20.1 || >3.20.1,<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,<5.0.0.dev0"
|
|
|
|
|
|
|
|
[package.extras]
|
|
|
|
grpc = ["grpcio (>=1.44.0,<2.0.0.dev0)"]
|
|
|
|
|
|
|
|
[[package]]
|
|
|
|
name = "grpc-interceptor"
|
2023-08-29 06:28:22 -06:00
|
|
|
version = "0.15.3"
|
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 = "Simplifies gRPC interceptors"
|
|
|
|
optional = false
|
|
|
|
python-versions = ">=3.7,<4.0"
|
|
|
|
files = [
|
2023-08-29 06:28:22 -06:00
|
|
|
{file = "grpc-interceptor-0.15.3.tar.gz", hash = "sha256:33592cb9d8c00fceed5755c71029f75aef55b273496dbced06f1d48f2571fcc3"},
|
|
|
|
{file = "grpc_interceptor-0.15.3-py3-none-any.whl", hash = "sha256:96be2043b7e49f9deb444f18b61c373ea28d22d81c90cd3b82127a4744eb9247"},
|
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"
|
2023-08-17 06:38:49 -06:00
|
|
|
version = "1.57.0"
|
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 = "HTTP/2-based RPC framework"
|
|
|
|
optional = false
|
|
|
|
python-versions = ">=3.7"
|
|
|
|
files = [
|
2023-08-17 06:38:49 -06:00
|
|
|
{file = "grpcio-1.57.0-cp310-cp310-linux_armv7l.whl", hash = "sha256:092fa155b945015754bdf988be47793c377b52b88d546e45c6a9f9579ac7f7b6"},
|
|
|
|
{file = "grpcio-1.57.0-cp310-cp310-macosx_12_0_universal2.whl", hash = "sha256:2f7349786da979a94690cc5c2b804cab4e8774a3cf59be40d037c4342c906649"},
|
|
|
|
{file = "grpcio-1.57.0-cp310-cp310-manylinux_2_17_aarch64.whl", hash = "sha256:82640e57fb86ea1d71ea9ab54f7e942502cf98a429a200b2e743d8672171734f"},
|
|
|
|
{file = "grpcio-1.57.0-cp310-cp310-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:40b72effd4c789de94ce1be2b5f88d7b9b5f7379fe9645f198854112a6567d9a"},
|
|
|
|
{file = "grpcio-1.57.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:2f708a6a17868ad8bf586598bee69abded4996b18adf26fd2d91191383b79019"},
|
|
|
|
{file = "grpcio-1.57.0-cp310-cp310-musllinux_1_1_i686.whl", hash = "sha256:60fe15288a0a65d5c1cb5b4a62b1850d07336e3ba728257a810317be14f0c527"},
|
|
|
|
{file = "grpcio-1.57.0-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:6907b1cf8bb29b058081d2aad677b15757a44ef2d4d8d9130271d2ad5e33efca"},
|
|
|
|
{file = "grpcio-1.57.0-cp310-cp310-win32.whl", hash = "sha256:57b183e8b252825c4dd29114d6c13559be95387aafc10a7be645462a0fc98bbb"},
|
|
|
|
{file = "grpcio-1.57.0-cp310-cp310-win_amd64.whl", hash = "sha256:7b400807fa749a9eb286e2cd893e501b110b4d356a218426cb9c825a0474ca56"},
|
|
|
|
{file = "grpcio-1.57.0-cp311-cp311-linux_armv7l.whl", hash = "sha256:c6ebecfb7a31385393203eb04ed8b6a08f5002f53df3d59e5e795edb80999652"},
|
|
|
|
{file = "grpcio-1.57.0-cp311-cp311-macosx_10_10_universal2.whl", hash = "sha256:00258cbe3f5188629828363ae8ff78477ce976a6f63fb2bb5e90088396faa82e"},
|
|
|
|
{file = "grpcio-1.57.0-cp311-cp311-manylinux_2_17_aarch64.whl", hash = "sha256:23e7d8849a0e58b806253fd206ac105b328171e01b8f18c7d5922274958cc87e"},
|
|
|
|
{file = "grpcio-1.57.0-cp311-cp311-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:5371bcd861e679d63b8274f73ac281751d34bd54eccdbfcd6aa00e692a82cd7b"},
|
|
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{file = "grpcio-1.57.0-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:7a635589201b18510ff988161b7b573f50c6a48fae9cb567657920ca82022b37"},
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{file = "grpcio-1.57.0-cp39-cp39-win32.whl", hash = "sha256:d78d8b86fcdfa1e4c21f8896614b6cc7ee01a2a758ec0c4382d662f2a62cf766"},
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{file = "grpcio-1.57.0-cp39-cp39-win_amd64.whl", hash = "sha256:20ec6fc4ad47d1b6e12deec5045ec3cd5402d9a1597f738263e98f490fe07056"},
|
|
|
|
{file = "grpcio-1.57.0.tar.gz", hash = "sha256:4b089f7ad1eb00a104078bab8015b0ed0ebcb3b589e527ab009c53893fd4e613"},
|
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]
|
2023-08-17 06:38:49 -06:00
|
|
|
protobuf = ["grpcio-tools (>=1.57.0)"]
|
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 = "grpcio-reflection"
|
2023-08-17 06:38:49 -06:00
|
|
|
version = "1.57.0"
|
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 = "Standard Protobuf Reflection Service for gRPC"
|
|
|
|
optional = false
|
|
|
|
python-versions = ">=3.6"
|
|
|
|
files = [
|
2023-08-17 06:38:49 -06:00
|
|
|
{file = "grpcio-reflection-1.57.0.tar.gz", hash = "sha256:8f63a18729cba995a172f8325235f5094cb066febec75f9a3b1b2e28328aa166"},
|
|
|
|
{file = "grpcio_reflection-1.57.0-py3-none-any.whl", hash = "sha256:d7deb8587f9d0095fb5d367c2aa5ce1380e3f23b0f8bca6c00bc404c5429cb6a"},
|
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]
|
2023-08-17 06:38:49 -06:00
|
|
|
grpcio = ">=1.57.0"
|
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
|
|
|
protobuf = ">=4.21.6"
|
|
|
|
|
|
|
|
[[package]]
|
|
|
|
name = "grpcio-status"
|
2023-08-17 06:38:49 -06:00
|
|
|
version = "1.57.0"
|
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 = "Status proto mapping for gRPC"
|
|
|
|
optional = false
|
|
|
|
python-versions = ">=3.6"
|
|
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|
files = [
|
2023-08-17 06:38:49 -06:00
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{file = "grpcio-status-1.57.0.tar.gz", hash = "sha256:b098da99df1eebe58337f8f78e50df990273ccacc1226fddeb47c590e3df9e02"},
|
|
|
|
{file = "grpcio_status-1.57.0-py3-none-any.whl", hash = "sha256:15d6af055914ebbc4ed17e55ebfb8e6bb17a45a57fea32e6af19978fb7844690"},
|
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
|
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[package.dependencies]
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|
googleapis-common-protos = ">=1.5.5"
|
2023-08-17 06:38:49 -06:00
|
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|
grpcio = ">=1.57.0"
|
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
|
|
|
protobuf = ">=4.21.6"
|
|
|
|
|
|
|
|
[[package]]
|
|
|
|
name = "grpcio-tools"
|
2023-08-17 06:38:49 -06:00
|
|
|
version = "1.57.0"
|
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 = "Protobuf code generator for gRPC"
|
|
|
|
optional = false
|
|
|
|
python-versions = ">=3.7"
|
|
|
|
files = [
|
2023-08-17 06:38:49 -06:00
|
|
|
{file = "grpcio-tools-1.57.0.tar.gz", hash = "sha256:2f16130d869ce27ecd623194547b649dd657333ec7e8644cc571c645781a9b85"},
|
|
|
|
{file = "grpcio_tools-1.57.0-cp310-cp310-linux_armv7l.whl", hash = "sha256:4fb8a8468031f858381a576078924af364a08833d8f8f3237018252c4573a802"},
|
|
|
|
{file = "grpcio_tools-1.57.0-cp310-cp310-macosx_12_0_universal2.whl", hash = "sha256:35bf0dad8a3562043345236c26d0053a856fb06c04d7da652f2ded914e508ae7"},
|
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{file = "grpcio_tools-1.57.0-cp310-cp310-manylinux_2_17_aarch64.whl", hash = "sha256:ec9aab2fb6783c7fc54bc28f58eb75f1ca77594e6b0fd5e5e7a8114a95169fe0"},
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{file = "grpcio_tools-1.57.0-cp310-cp310-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:0cf5fc0a1c23f8ea34b408b72fb0e90eec0f404ad4dba98e8f6da3c9ce34e2ed"},
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{file = "grpcio_tools-1.57.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:26e69d08a515554e0cfe1ec4d31568836f4b17f0ff82294f957f629388629eb9"},
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{file = "grpcio_tools-1.57.0-cp310-cp310-musllinux_1_1_i686.whl", hash = "sha256:c39a3656576b6fdaaf28abe0467f7a7231df4230c1bee132322dbc3209419e7f"},
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{file = "grpcio_tools-1.57.0-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:f64f8ab22d27d4a5693310748d35a696061c3b5c7b8c4fb4ab3b4bc1068b6b56"},
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{file = "grpcio_tools-1.57.0-cp310-cp310-win32.whl", hash = "sha256:d2a134756f4db34759a5cc7f7e43f7eb87540b68d1cca62925593c6fb93924f7"},
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{file = "grpcio_tools-1.57.0-cp310-cp310-win_amd64.whl", hash = "sha256:9a3d60fb8d46ede26c1907c146561b3a9caa20a7aff961bc661ef8226f85a2e9"},
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{file = "grpcio_tools-1.57.0-cp311-cp311-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:ed85a0291fff45b67f2557fe7f117d3bc7af8b54b8619d27bf374b5c8b7e3ca2"},
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{file = "grpcio_tools-1.57.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:e868cd6feb3ef07d4b35be104fe1fd0657db05259ff8f8ec5e08f4f89ca1191d"},
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{file = "grpcio_tools-1.57.0-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:8a42dc220eb5305f470855c9284f4c8e85ae59d6d742cd07946b0cbe5e9ca186"},
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{file = "grpcio_tools-1.57.0-cp38-cp38-musllinux_1_1_i686.whl", hash = "sha256:90d10d9038ba46a595a223a34f136c9230e3d6d7abc2433dbf0e1c31939d3a8b"},
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{file = "grpcio_tools-1.57.0-cp38-cp38-musllinux_1_1_x86_64.whl", hash = "sha256:5bc3e6d338aefb052e19cedabe00452be46d0c10a4ed29ee77abb00402e438fe"},
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{file = "grpcio_tools-1.57.0-cp38-cp38-win32.whl", hash = "sha256:34b36217b17b5bea674a414229913e1fd80ede328be51e1b531fcc62abd393b0"},
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{file = "grpcio_tools-1.57.0-cp38-cp38-win_amd64.whl", hash = "sha256:dbde4004a0688400036342ff73e3706e8940483e2871547b1354d59e93a38277"},
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{file = "grpcio_tools-1.57.0-cp39-cp39-linux_armv7l.whl", hash = "sha256:784574709b9690dc28696617ea69352e2132352fdfc9bc89afa8e39f99ae538e"},
|
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{file = "grpcio_tools-1.57.0-cp39-cp39-macosx_10_10_universal2.whl", hash = "sha256:85ac4e62eb44428cde025fd9ab7554002315fc7880f791c553fc5a0015cc9931"},
|
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|
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{file = "grpcio_tools-1.57.0-cp39-cp39-manylinux_2_17_aarch64.whl", hash = "sha256:dc771d4db5701f280957bbcee91745e0686d00ed1c6aa7e05ba30a58b02d70a1"},
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{file = "grpcio_tools-1.57.0-cp39-cp39-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:f3ac06703c412f8167a9062eaf6099409967e33bf98fa5b02be4b4689b6bdf39"},
|
|
|
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{file = "grpcio_tools-1.57.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:02d78c034109f46032c7217260066d49d41e6bcaf588fa28fa40fe2f83445347"},
|
|
|
|
{file = "grpcio_tools-1.57.0-cp39-cp39-musllinux_1_1_i686.whl", hash = "sha256:2db25f15ed44327f2e02d0c4fe741ac966f9500e407047d8a7c7fccf2df65616"},
|
|
|
|
{file = "grpcio_tools-1.57.0-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:2b417c97936d94874a3ce7ed8deab910f2233e3612134507cfee4af8735c38a6"},
|
|
|
|
{file = "grpcio_tools-1.57.0-cp39-cp39-win32.whl", hash = "sha256:f717cce5093e6b6049d9ea6d12fdf3658efdb1a80772f7737db1f8510b876df6"},
|
|
|
|
{file = "grpcio_tools-1.57.0-cp39-cp39-win_amd64.whl", hash = "sha256:1c0e8a1a32973a5d59fbcc19232f925e5c48116e9411f788033a31c5ca5130b4"},
|
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]
|
2023-08-17 06:38:49 -06:00
|
|
|
grpcio = ">=1.57.0"
|
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
|
|
|
protobuf = ">=4.21.6,<5.0dev"
|
|
|
|
setuptools = "*"
|
|
|
|
|
|
|
|
[[package]]
|
|
|
|
name = "hf-transfer"
|
|
|
|
version = "0.1.3"
|
|
|
|
description = ""
|
|
|
|
optional = false
|
|
|
|
python-versions = ">=3.7"
|
|
|
|
files = [
|
2023-07-04 12:23:55 -06:00
|
|
|
{file = "hf_transfer-0.1.3-cp310-cp310-macosx_10_9_x86_64.macosx_11_0_arm64.macosx_10_9_universal2.whl", hash = "sha256:862b6ddba8e236bdc73408c20d020cfe5069cac3fd0b6de901c46f031df2b7d9"},
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{file = "hf_transfer-0.1.3-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:569ef1ec6fec182e706ade4ea0c63f8510fd618ed7ced7c772efaafac7245b07"},
|
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{file = "hf_transfer-0.1.3-cp310-none-win_amd64.whl", hash = "sha256:c9faa88b3491c50d4aa75faf18ae24040cd91aa0565c7f7ba2357dbcbf8372f6"},
|
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{file = "hf_transfer-0.1.3-cp311-cp311-macosx_10_9_x86_64.macosx_11_0_arm64.macosx_10_9_universal2.whl", hash = "sha256:d53954ecfaadc84c15481bf5d4c7282323196b4b6df1d1be54208d4fdedfb407"},
|
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|
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{file = "hf_transfer-0.1.3-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:334862f4a82f8a09d6d3f550e67d7e498bb8882e678b7725638254fed3276801"},
|
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{file = "hf_transfer-0.1.3-cp311-none-win_amd64.whl", hash = "sha256:da92a1483a66cf2baa96de133c75e7d5d9a60e4a0e60d228f26c573c73a1feb6"},
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{file = "hf_transfer-0.1.3-cp37-cp37m-macosx_10_9_x86_64.macosx_11_0_arm64.macosx_10_9_universal2.whl", hash = "sha256:617692a70cf299576d82cfc860923f29ec5c834a3f5242bc0853d4f106670398"},
|
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{file = "hf_transfer-0.1.3-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:ca218fb6efc5c22379d9e64989e84bff426fcf5664fdbbf7cd70aa8b79497652"},
|
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{file = "hf_transfer-0.1.3-cp37-none-win_amd64.whl", hash = "sha256:6e5201b648df6106c232fcdb507db734081fd6220dfb1c432bd27c6fa9453331"},
|
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{file = "hf_transfer-0.1.3-cp38-cp38-macosx_10_9_x86_64.macosx_11_0_arm64.macosx_10_9_universal2.whl", hash = "sha256:445edfcd9d59c9d2541957177a9c9225b1f0e8855f6311fb16e20f67c3426421"},
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{file = "hf_transfer-0.1.3-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:0c1bdfa554f0b0936c1623b99058c6998a00fdcd86f75d9203f3f66572d2e30c"},
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{file = "hf_transfer-0.1.3-cp38-none-win_amd64.whl", hash = "sha256:606f2fe436e5be73f07987a56cd97c695805413d29203ae39ebd9fc596405435"},
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{file = "hf_transfer-0.1.3-cp39-cp39-macosx_10_9_x86_64.macosx_11_0_arm64.macosx_10_9_universal2.whl", hash = "sha256:9913f5ad2644a1f57c1b7755a7d959ca5e0189863bb0473817d0707af230bf6a"},
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{file = "hf_transfer-0.1.3-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:d935946791e338f748e05a23df877d74fbcd39dc7b537f0aa2e5a5841cf7dde8"},
|
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{file = "hf_transfer-0.1.3-cp39-none-win_amd64.whl", hash = "sha256:79099ac043423b263a2843a24213418f309d5c8bc458776622bffe012ebced73"},
|
|
|
|
{file = "hf_transfer-0.1.3-pp37-pypy37_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:3ce6c5965a57d94db5e043aa488a4df929a32000db125d9c9a1d325e8c7006dc"},
|
|
|
|
{file = "hf_transfer-0.1.3-pp38-pypy38_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:8a7934c8e491bb395731f677f66dd5f6641432f338a3a9efc9f0b6c186d37cf8"},
|
|
|
|
{file = "hf_transfer-0.1.3-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:efb8b41360c7e3d7700c147b70688aed0a03e86fbe5bcfdee079b0e634f026f9"},
|
|
|
|
{file = "hf_transfer-0.1.3.tar.gz", hash = "sha256:7afd7eb03efad7812a48591b639b2e3f3d1f93c1e9060c18cc63ebf08d7e193c"},
|
|
|
|
]
|
feat(server): Add native support for PEFT Lora models (#762)
- Will detect `peft` model by finding `adapter_config.json`.
- This triggers a totally dedicated `download-weights` path
- This path, loads the adapter config, finds the base model_id
- It loads the base_model
- Then peft_model
- Then `merge_and_unload()`
- Then `save_pretrained(.., safe_serialization=True)
- Add back the config + tokenizer.merge_and_unload()`
- Then `save_pretrained(.., safe_serialization=True)
- Add back the config + tokenizer.
- The chosen location is a **local folder with the name of the user
chosen model id**
PROs:
- Easier than to expect user to merge manually
- Barely any change outside of `download-weights` command.
- This means everything will work in a single load.
- Should enable out of the box SM + HFE
CONs:
- Creates a local merged model in unusual location, potentially
not saved across docker reloads, or ovewriting some files if the PEFT
itself was local and containing other files in addition to the lora
Alternatives considered:
- Add `local_files_only=True` every where (discard because of massive
code change for not a good enough reason)
- Return something to `launcher` about the new model-id (a cleaner
location for this new model), but it would
introduce new communication somewhere where we didn't need it before.
- Using the HF cache folder and *stopping* the flow after
`download-weights` and asking user to restart with the actual local
model location
Fix #482
# What does this PR do?
<!--
Congratulations! You've made it this far! You're not quite done yet
though.
Once merged, your PR is going to appear in the release notes with the
title you set, so make sure it's a great title that fully reflects the
extent of your awesome contribution.
Then, please replace this with a description of the change and which
issue is fixed (if applicable). Please also include relevant motivation
and context. List any dependencies (if any) that are required for this
change.
Once you're done, someone will review your PR shortly (see the section
"Who can review?" below to tag some potential reviewers). They may
suggest changes to make the code even better. If no one reviewed your PR
after a week has passed, don't hesitate to post a new comment
@-mentioning the same persons---sometimes notifications get lost.
-->
<!-- Remove if not applicable -->
Fixes # (issue)
## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the
other checks if that's the case).
- [ ] Did you read the [contributor
guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests),
Pull Request section?
- [ ] Was this discussed/approved via a Github issue or the
[forum](https://discuss.huggingface.co/)? Please add a link
to it if that's the case.
- [ ] Did you make sure to update the documentation with your changes?
Here are the
[documentation
guidelines](https://github.com/huggingface/transformers/tree/main/docs),
and
[here are tips on formatting
docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation).
- [ ] Did you write any new necessary tests?
## Who can review?
Anyone in the community is free to review the PR once the tests have
passed. Feel free to tag
members/contributors who may be interested in your PR.
<!-- Your PR will be replied to 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"
|
2023-08-29 06:28:22 -06:00
|
|
|
version = "0.16.4"
|
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 = "Client library to download and publish models, datasets and other repos on the huggingface.co hub"
|
|
|
|
optional = false
|
|
|
|
python-versions = ">=3.7.0"
|
|
|
|
files = [
|
2023-08-29 06:28:22 -06:00
|
|
|
{file = "huggingface_hub-0.16.4-py3-none-any.whl", hash = "sha256:0d3df29932f334fead024afc7cb4cc5149d955238b8b5e42dcf9740d6995a349"},
|
|
|
|
{file = "huggingface_hub-0.16.4.tar.gz", hash = "sha256:608c7d4f3d368b326d1747f91523dbd1f692871e8e2e7a4750314a2dd8b63e14"},
|
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 = "*"
|
|
|
|
fsspec = "*"
|
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|
packaging = ">=20.9"
|
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|
|
pyyaml = ">=5.1"
|
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|
requests = "*"
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tqdm = ">=4.42.1"
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|
typing-extensions = ">=3.7.4.3"
|
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|
|
[package.extras]
|
2023-08-29 06:28:22 -06:00
|
|
|
all = ["InquirerPy (==0.3.4)", "Jinja2", "Pillow", "aiohttp", "black (>=23.1,<24.0)", "gradio", "jedi", "mypy (==0.982)", "numpy", "pydantic", "pytest", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-vcr", "pytest-xdist", "ruff (>=0.0.241)", "soundfile", "types-PyYAML", "types-requests", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "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)"]
|
2023-08-29 06:28:22 -06:00
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dev = ["InquirerPy (==0.3.4)", "Jinja2", "Pillow", "aiohttp", "black (>=23.1,<24.0)", "gradio", "jedi", "mypy (==0.982)", "numpy", "pydantic", "pytest", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-vcr", "pytest-xdist", "ruff (>=0.0.241)", "soundfile", "types-PyYAML", "types-requests", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "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"]
|
2023-08-29 06:28:22 -06:00
|
|
|
inference = ["aiohttp", "pydantic"]
|
feat(server): Add native support for PEFT Lora models (#762)
- Will detect `peft` model by finding `adapter_config.json`.
- This triggers a totally dedicated `download-weights` path
- This path, loads the adapter config, finds the base model_id
- It loads the base_model
- Then peft_model
- Then `merge_and_unload()`
- Then `save_pretrained(.., safe_serialization=True)
- Add back the config + tokenizer.merge_and_unload()`
- Then `save_pretrained(.., safe_serialization=True)
- Add back the config + tokenizer.
- The chosen location is a **local folder with the name of the user
chosen model id**
PROs:
- Easier than to expect user to merge manually
- Barely any change outside of `download-weights` command.
- This means everything will work in a single load.
- Should enable out of the box SM + HFE
CONs:
- Creates a local merged model in unusual location, potentially
not saved across docker reloads, or ovewriting some files if the PEFT
itself was local and containing other files in addition to the lora
Alternatives considered:
- Add `local_files_only=True` every where (discard because of massive
code change for not a good enough reason)
- Return something to `launcher` about the new model-id (a cleaner
location for this new model), but it would
introduce new communication somewhere where we didn't need it before.
- Using the HF cache folder and *stopping* the flow after
`download-weights` and asking user to restart with the actual local
model location
Fix #482
# What does this PR do?
<!--
Congratulations! You've made it this far! You're not quite done yet
though.
Once merged, your PR is going to appear in the release notes with the
title you set, so make sure it's a great title that fully reflects the
extent of your awesome contribution.
Then, please replace this with a description of the change and which
issue is fixed (if applicable). Please also include relevant motivation
and context. List any dependencies (if any) that are required for this
change.
Once you're done, someone will review your PR shortly (see the section
"Who can review?" below to tag some potential reviewers). They may
suggest changes to make the code even better. If no one reviewed your PR
after a week has passed, don't hesitate to post a new comment
@-mentioning the same persons---sometimes notifications get lost.
-->
<!-- Remove if not applicable -->
Fixes # (issue)
## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the
other checks if that's the case).
- [ ] Did you read the [contributor
guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests),
Pull Request section?
- [ ] Was this discussed/approved via a Github issue or the
[forum](https://discuss.huggingface.co/)? Please add a link
to it if that's the case.
- [ ] Did you make sure to update the documentation with your changes?
Here are the
[documentation
guidelines](https://github.com/huggingface/transformers/tree/main/docs),
and
[here are tips on formatting
docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation).
- [ ] Did you write any new necessary tests?
## Who can review?
Anyone in the community is free to review the PR once the tests have
passed. Feel free to tag
members/contributors who may be interested in your PR.
<!-- Your PR will be replied to 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 (>=23.1,<24.0)", "mypy (==0.982)", "ruff (>=0.0.241)"]
|
|
|
|
tensorflow = ["graphviz", "pydot", "tensorflow"]
|
2023-08-29 06:28:22 -06:00
|
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|
testing = ["InquirerPy (==0.3.4)", "Jinja2", "Pillow", "aiohttp", "gradio", "jedi", "numpy", "pydantic", "pytest", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-vcr", "pytest-xdist", "soundfile", "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
|
|
|
torch = ["torch"]
|
2023-08-29 06:28:22 -06:00
|
|
|
typing = ["pydantic", "types-PyYAML", "types-requests", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3"]
|
feat(server): Add native support for PEFT Lora models (#762)
- Will detect `peft` model by finding `adapter_config.json`.
- This triggers a totally dedicated `download-weights` path
- This path, loads the adapter config, finds the base model_id
- It loads the base_model
- Then peft_model
- Then `merge_and_unload()`
- Then `save_pretrained(.., safe_serialization=True)
- Add back the config + tokenizer.merge_and_unload()`
- Then `save_pretrained(.., safe_serialization=True)
- Add back the config + tokenizer.
- The chosen location is a **local folder with the name of the user
chosen model id**
PROs:
- Easier than to expect user to merge manually
- Barely any change outside of `download-weights` command.
- This means everything will work in a single load.
- Should enable out of the box SM + HFE
CONs:
- Creates a local merged model in unusual location, potentially
not saved across docker reloads, or ovewriting some files if the PEFT
itself was local and containing other files in addition to the lora
Alternatives considered:
- Add `local_files_only=True` every where (discard because of massive
code change for not a good enough reason)
- Return something to `launcher` about the new model-id (a cleaner
location for this new model), but it would
introduce new communication somewhere where we didn't need it before.
- Using the HF cache folder and *stopping* the flow after
`download-weights` and asking user to restart with the actual local
model location
Fix #482
# What does this PR do?
<!--
Congratulations! You've made it this far! You're not quite done yet
though.
Once merged, your PR is going to appear in the release notes with the
title you set, so make sure it's a great title that fully reflects the
extent of your awesome contribution.
Then, please replace this with a description of the change and which
issue is fixed (if applicable). Please also include relevant motivation
and context. List any dependencies (if any) that are required for this
change.
Once you're done, someone will review your PR shortly (see the section
"Who can review?" below to tag some potential reviewers). They may
suggest changes to make the code even better. If no one reviewed your PR
after a week has passed, don't hesitate to post a new comment
@-mentioning the same persons---sometimes notifications get lost.
-->
<!-- Remove if not applicable -->
Fixes # (issue)
## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the
other checks if that's the case).
- [ ] Did you read the [contributor
guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests),
Pull Request section?
- [ ] Was this discussed/approved via a Github issue or the
[forum](https://discuss.huggingface.co/)? Please add a link
to it if that's the case.
- [ ] Did you make sure to update the documentation with your changes?
Here are the
[documentation
guidelines](https://github.com/huggingface/transformers/tree/main/docs),
and
[here are tips on formatting
docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation).
- [ ] Did you write any new necessary tests?
## Who can review?
Anyone in the community is free to review the PR once the tests have
passed. Feel free to tag
members/contributors who may be interested in your PR.
<!-- Your PR will be replied to 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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|
|
[[package]]
|
|
|
|
name = "idna"
|
|
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|
version = "3.4"
|
|
|
|
description = "Internationalized Domain Names in Applications (IDNA)"
|
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|
optional = false
|
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|
python-versions = ">=3.5"
|
|
|
|
files = [
|
2023-07-04 12:23:55 -06:00
|
|
|
{file = "idna-3.4-py3-none-any.whl", hash = "sha256:90b77e79eaa3eba6de819a0c442c0b4ceefc341a7a2ab77d7562bf49f425c5c2"},
|
|
|
|
{file = "idna-3.4.tar.gz", hash = "sha256:814f528e8dead7d329833b91c5faa87d60bf71824cd12a7530b5526063d02cb4"},
|
|
|
|
]
|
feat(server): Add native support for PEFT Lora models (#762)
- Will detect `peft` model by finding `adapter_config.json`.
- This triggers a totally dedicated `download-weights` path
- This path, loads the adapter config, finds the base model_id
- It loads the base_model
- Then peft_model
- Then `merge_and_unload()`
- Then `save_pretrained(.., safe_serialization=True)
- Add back the config + tokenizer.merge_and_unload()`
- Then `save_pretrained(.., safe_serialization=True)
- Add back the config + tokenizer.
- The chosen location is a **local folder with the name of the user
chosen model id**
PROs:
- Easier than to expect user to merge manually
- Barely any change outside of `download-weights` command.
- This means everything will work in a single load.
- Should enable out of the box SM + HFE
CONs:
- Creates a local merged model in unusual location, potentially
not saved across docker reloads, or ovewriting some files if the PEFT
itself was local and containing other files in addition to the lora
Alternatives considered:
- Add `local_files_only=True` every where (discard because of massive
code change for not a good enough reason)
- Return something to `launcher` about the new model-id (a cleaner
location for this new model), but it would
introduce new communication somewhere where we didn't need it before.
- Using the HF cache folder and *stopping* the flow after
`download-weights` and asking user to restart with the actual local
model location
Fix #482
# What does this PR do?
<!--
Congratulations! You've made it this far! You're not quite done yet
though.
Once merged, your PR is going to appear in the release notes with the
title you set, so make sure it's a great title that fully reflects the
extent of your awesome contribution.
Then, please replace this with a description of the change and which
issue is fixed (if applicable). Please also include relevant motivation
and context. List any dependencies (if any) that are required for this
change.
Once you're done, someone will review your PR shortly (see the section
"Who can review?" below to tag some potential reviewers). They may
suggest changes to make the code even better. If no one reviewed your PR
after a week has passed, don't hesitate to post a new comment
@-mentioning the same persons---sometimes notifications get lost.
-->
<!-- Remove if not applicable -->
Fixes # (issue)
## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the
other checks if that's the case).
- [ ] Did you read the [contributor
guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests),
Pull Request section?
- [ ] Was this discussed/approved via a Github issue or the
[forum](https://discuss.huggingface.co/)? Please add a link
to it if that's the case.
- [ ] Did you make sure to update the documentation with your changes?
Here are the
[documentation
guidelines](https://github.com/huggingface/transformers/tree/main/docs),
and
[here are tips on formatting
docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation).
- [ ] Did you write any new necessary tests?
## Who can review?
Anyone in the community is free to review the PR once the tests have
passed. Feel free to tag
members/contributors who may be interested in your PR.
<!-- Your PR will be replied to 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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[[package]]
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name = "iniconfig"
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|
version = "2.0.0"
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description = "brain-dead simple config-ini parsing"
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optional = false
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python-versions = ">=3.7"
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files = [
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2023-07-04 12:23:55 -06:00
|
|
|
{file = "iniconfig-2.0.0-py3-none-any.whl", hash = "sha256:b6a85871a79d2e3b22d2d1b94ac2824226a63c6b741c88f7ae975f18b6778374"},
|
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|
{file = "iniconfig-2.0.0.tar.gz", hash = "sha256:2d91e135bf72d31a410b17c16da610a82cb55f6b0477d1a902134b24a455b8b3"},
|
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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
|
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|
[[package]]
|
2023-08-03 13:54:39 -06:00
|
|
|
name = "jinja2"
|
feat(server): Add native support for PEFT Lora models (#762)
- Will detect `peft` model by finding `adapter_config.json`.
- This triggers a totally dedicated `download-weights` path
- This path, loads the adapter config, finds the base model_id
- It loads the base_model
- Then peft_model
- Then `merge_and_unload()`
- Then `save_pretrained(.., safe_serialization=True)
- Add back the config + tokenizer.merge_and_unload()`
- Then `save_pretrained(.., safe_serialization=True)
- Add back the config + tokenizer.
- The chosen location is a **local folder with the name of the user
chosen model id**
PROs:
- Easier than to expect user to merge manually
- Barely any change outside of `download-weights` command.
- This means everything will work in a single load.
- Should enable out of the box SM + HFE
CONs:
- Creates a local merged model in unusual location, potentially
not saved across docker reloads, or ovewriting some files if the PEFT
itself was local and containing other files in addition to the lora
Alternatives considered:
- Add `local_files_only=True` every where (discard because of massive
code change for not a good enough reason)
- Return something to `launcher` about the new model-id (a cleaner
location for this new model), but it would
introduce new communication somewhere where we didn't need it before.
- Using the HF cache folder and *stopping* the flow after
`download-weights` and asking user to restart with the actual local
model location
Fix #482
# What does this PR do?
<!--
Congratulations! You've made it this far! You're not quite done yet
though.
Once merged, your PR is going to appear in the release notes with the
title you set, so make sure it's a great title that fully reflects the
extent of your awesome contribution.
Then, please replace this with a description of the change and which
issue is fixed (if applicable). Please also include relevant motivation
and context. List any dependencies (if any) that are required for this
change.
Once you're done, someone will review your PR shortly (see the section
"Who can review?" below to tag some potential reviewers). They may
suggest changes to make the code even better. If no one reviewed your PR
after a week has passed, don't hesitate to post a new comment
@-mentioning the same persons---sometimes notifications get lost.
-->
<!-- Remove if not applicable -->
Fixes # (issue)
## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the
other checks if that's the case).
- [ ] Did you read the [contributor
guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests),
Pull Request section?
- [ ] Was this discussed/approved via a Github issue or the
[forum](https://discuss.huggingface.co/)? Please add a link
to it if that's the case.
- [ ] Did you make sure to update the documentation with your changes?
Here are the
[documentation
guidelines](https://github.com/huggingface/transformers/tree/main/docs),
and
[here are tips on formatting
docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation).
- [ ] Did you write any new necessary tests?
## Who can review?
Anyone in the community is free to review the PR once the tests have
passed. Feel free to tag
members/contributors who may be interested in your PR.
<!-- Your PR will be replied to 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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version = "3.1.2"
|
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description = "A very fast and expressive template engine."
|
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optional = false
|
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|
python-versions = ">=3.7"
|
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files = [
|
2023-07-04 12:23:55 -06:00
|
|
|
{file = "Jinja2-3.1.2-py3-none-any.whl", hash = "sha256:6088930bfe239f0e6710546ab9c19c9ef35e29792895fed6e6e31a023a182a61"},
|
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|
|
{file = "Jinja2-3.1.2.tar.gz", hash = "sha256:31351a702a408a9e7595a8fc6150fc3f43bb6bf7e319770cbc0db9df9437e852"},
|
|
|
|
]
|
feat(server): Add native support for PEFT Lora models (#762)
- Will detect `peft` model by finding `adapter_config.json`.
- This triggers a totally dedicated `download-weights` path
- This path, loads the adapter config, finds the base model_id
- It loads the base_model
- Then peft_model
- Then `merge_and_unload()`
- Then `save_pretrained(.., safe_serialization=True)
- Add back the config + tokenizer.merge_and_unload()`
- Then `save_pretrained(.., safe_serialization=True)
- Add back the config + tokenizer.
- The chosen location is a **local folder with the name of the user
chosen model id**
PROs:
- Easier than to expect user to merge manually
- Barely any change outside of `download-weights` command.
- This means everything will work in a single load.
- Should enable out of the box SM + HFE
CONs:
- Creates a local merged model in unusual location, potentially
not saved across docker reloads, or ovewriting some files if the PEFT
itself was local and containing other files in addition to the lora
Alternatives considered:
- Add `local_files_only=True` every where (discard because of massive
code change for not a good enough reason)
- Return something to `launcher` about the new model-id (a cleaner
location for this new model), but it would
introduce new communication somewhere where we didn't need it before.
- Using the HF cache folder and *stopping* the flow after
`download-weights` and asking user to restart with the actual local
model location
Fix #482
# What does this PR do?
<!--
Congratulations! You've made it this far! You're not quite done yet
though.
Once merged, your PR is going to appear in the release notes with the
title you set, so make sure it's a great title that fully reflects the
extent of your awesome contribution.
Then, please replace this with a description of the change and which
issue is fixed (if applicable). Please also include relevant motivation
and context. List any dependencies (if any) that are required for this
change.
Once you're done, someone will review your PR shortly (see the section
"Who can review?" below to tag some potential reviewers). They may
suggest changes to make the code even better. If no one reviewed your PR
after a week has passed, don't hesitate to post a new comment
@-mentioning the same persons---sometimes notifications get lost.
-->
<!-- Remove if not applicable -->
Fixes # (issue)
## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the
other checks if that's the case).
- [ ] Did you read the [contributor
guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests),
Pull Request section?
- [ ] Was this discussed/approved via a Github issue or the
[forum](https://discuss.huggingface.co/)? Please add a link
to it if that's the case.
- [ ] Did you make sure to update the documentation with your changes?
Here are the
[documentation
guidelines](https://github.com/huggingface/transformers/tree/main/docs),
and
[here are tips on formatting
docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation).
- [ ] Did you write any new necessary tests?
## Who can review?
Anyone in the community is free to review the PR once the tests have
passed. Feel free to tag
members/contributors who may be interested in your PR.
<!-- Your PR will be replied to 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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|
|
|
|
|
[package.dependencies]
|
|
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|
MarkupSafe = ">=2.0"
|
|
|
|
|
|
|
|
[package.extras]
|
|
|
|
i18n = ["Babel (>=2.7)"]
|
|
|
|
|
|
|
|
[[package]]
|
|
|
|
name = "loguru"
|
|
|
|
version = "0.6.0"
|
|
|
|
description = "Python logging made (stupidly) simple"
|
|
|
|
optional = false
|
|
|
|
python-versions = ">=3.5"
|
|
|
|
files = [
|
2023-07-04 12:23:55 -06:00
|
|
|
{file = "loguru-0.6.0-py3-none-any.whl", hash = "sha256:4e2414d534a2ab57573365b3e6d0234dfb1d84b68b7f3b948e6fb743860a77c3"},
|
|
|
|
{file = "loguru-0.6.0.tar.gz", hash = "sha256:066bd06758d0a513e9836fd9c6b5a75bfb3fd36841f4b996bc60b547a309d41c"},
|
|
|
|
]
|
feat(server): Add native support for PEFT Lora models (#762)
- Will detect `peft` model by finding `adapter_config.json`.
- This triggers a totally dedicated `download-weights` path
- This path, loads the adapter config, finds the base model_id
- It loads the base_model
- Then peft_model
- Then `merge_and_unload()`
- Then `save_pretrained(.., safe_serialization=True)
- Add back the config + tokenizer.merge_and_unload()`
- Then `save_pretrained(.., safe_serialization=True)
- Add back the config + tokenizer.
- The chosen location is a **local folder with the name of the user
chosen model id**
PROs:
- Easier than to expect user to merge manually
- Barely any change outside of `download-weights` command.
- This means everything will work in a single load.
- Should enable out of the box SM + HFE
CONs:
- Creates a local merged model in unusual location, potentially
not saved across docker reloads, or ovewriting some files if the PEFT
itself was local and containing other files in addition to the lora
Alternatives considered:
- Add `local_files_only=True` every where (discard because of massive
code change for not a good enough reason)
- Return something to `launcher` about the new model-id (a cleaner
location for this new model), but it would
introduce new communication somewhere where we didn't need it before.
- Using the HF cache folder and *stopping* the flow after
`download-weights` and asking user to restart with the actual local
model location
Fix #482
# What does this PR do?
<!--
Congratulations! You've made it this far! You're not quite done yet
though.
Once merged, your PR is going to appear in the release notes with the
title you set, so make sure it's a great title that fully reflects the
extent of your awesome contribution.
Then, please replace this with a description of the change and which
issue is fixed (if applicable). Please also include relevant motivation
and context. List any dependencies (if any) that are required for this
change.
Once you're done, someone will review your PR shortly (see the section
"Who can review?" below to tag some potential reviewers). They may
suggest changes to make the code even better. If no one reviewed your PR
after a week has passed, don't hesitate to post a new comment
@-mentioning the same persons---sometimes notifications get lost.
-->
<!-- Remove if not applicable -->
Fixes # (issue)
## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the
other checks if that's the case).
- [ ] Did you read the [contributor
guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests),
Pull Request section?
- [ ] Was this discussed/approved via a Github issue or the
[forum](https://discuss.huggingface.co/)? Please add a link
to it if that's the case.
- [ ] Did you make sure to update the documentation with your changes?
Here are the
[documentation
guidelines](https://github.com/huggingface/transformers/tree/main/docs),
and
[here are tips on formatting
docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation).
- [ ] Did you write any new necessary tests?
## Who can review?
Anyone in the community is free to review the PR once the tests have
passed. Feel free to tag
members/contributors who may be interested in your PR.
<!-- Your PR will be replied to 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)"]
|
|
|
|
|
|
|
|
[[package]]
|
2023-08-03 13:54:39 -06:00
|
|
|
name = "markupsafe"
|
feat(server): Add native support for PEFT Lora models (#762)
- Will detect `peft` model by finding `adapter_config.json`.
- This triggers a totally dedicated `download-weights` path
- This path, loads the adapter config, finds the base model_id
- It loads the base_model
- Then peft_model
- Then `merge_and_unload()`
- Then `save_pretrained(.., safe_serialization=True)
- Add back the config + tokenizer.merge_and_unload()`
- Then `save_pretrained(.., safe_serialization=True)
- Add back the config + tokenizer.
- The chosen location is a **local folder with the name of the user
chosen model id**
PROs:
- Easier than to expect user to merge manually
- Barely any change outside of `download-weights` command.
- This means everything will work in a single load.
- Should enable out of the box SM + HFE
CONs:
- Creates a local merged model in unusual location, potentially
not saved across docker reloads, or ovewriting some files if the PEFT
itself was local and containing other files in addition to the lora
Alternatives considered:
- Add `local_files_only=True` every where (discard because of massive
code change for not a good enough reason)
- Return something to `launcher` about the new model-id (a cleaner
location for this new model), but it would
introduce new communication somewhere where we didn't need it before.
- Using the HF cache folder and *stopping* the flow after
`download-weights` and asking user to restart with the actual local
model location
Fix #482
# What does this PR do?
<!--
Congratulations! You've made it this far! You're not quite done yet
though.
Once merged, your PR is going to appear in the release notes with the
title you set, so make sure it's a great title that fully reflects the
extent of your awesome contribution.
Then, please replace this with a description of the change and which
issue is fixed (if applicable). Please also include relevant motivation
and context. List any dependencies (if any) that are required for this
change.
Once you're done, someone will review your PR shortly (see the section
"Who can review?" below to tag some potential reviewers). They may
suggest changes to make the code even better. If no one reviewed your PR
after a week has passed, don't hesitate to post a new comment
@-mentioning the same persons---sometimes notifications get lost.
-->
<!-- Remove if not applicable -->
Fixes # (issue)
## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the
other checks if that's the case).
- [ ] Did you read the [contributor
guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests),
Pull Request section?
- [ ] Was this discussed/approved via a Github issue or the
[forum](https://discuss.huggingface.co/)? Please add a link
to it if that's the case.
- [ ] Did you make sure to update the documentation with your changes?
Here are the
[documentation
guidelines](https://github.com/huggingface/transformers/tree/main/docs),
and
[here are tips on formatting
docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation).
- [ ] Did you write any new necessary tests?
## Who can review?
Anyone in the community is free to review the PR once the tests have
passed. Feel free to tag
members/contributors who may be interested in your PR.
<!-- Your PR will be replied to 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 = "2.1.3"
|
|
|
|
description = "Safely add untrusted strings to HTML/XML markup."
|
|
|
|
optional = false
|
|
|
|
python-versions = ">=3.7"
|
|
|
|
files = [
|
2023-07-04 12:23:55 -06:00
|
|
|
{file = "MarkupSafe-2.1.3-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:cd0f502fe016460680cd20aaa5a76d241d6f35a1c3350c474bac1273803893fa"},
|
|
|
|
{file = "MarkupSafe-2.1.3-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:e09031c87a1e51556fdcb46e5bd4f59dfb743061cf93c4d6831bf894f125eb57"},
|
|
|
|
{file = "MarkupSafe-2.1.3-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:68e78619a61ecf91e76aa3e6e8e33fc4894a2bebe93410754bd28fce0a8a4f9f"},
|
|
|
|
{file = "MarkupSafe-2.1.3-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:65c1a9bcdadc6c28eecee2c119465aebff8f7a584dd719facdd9e825ec61ab52"},
|
|
|
|
{file = "MarkupSafe-2.1.3-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:525808b8019e36eb524b8c68acdd63a37e75714eac50e988180b169d64480a00"},
|
|
|
|
{file = "MarkupSafe-2.1.3-cp310-cp310-musllinux_1_1_aarch64.whl", hash = "sha256:962f82a3086483f5e5f64dbad880d31038b698494799b097bc59c2edf392fce6"},
|
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{file = "MarkupSafe-2.1.3-cp310-cp310-musllinux_1_1_i686.whl", hash = "sha256:aa7bd130efab1c280bed0f45501b7c8795f9fdbeb02e965371bbef3523627779"},
|
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|
{file = "MarkupSafe-2.1.3-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:c9c804664ebe8f83a211cace637506669e7890fec1b4195b505c214e50dd4eb7"},
|
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{file = "MarkupSafe-2.1.3-cp310-cp310-win32.whl", hash = "sha256:10bbfe99883db80bdbaff2dcf681dfc6533a614f700da1287707e8a5d78a8431"},
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{file = "MarkupSafe-2.1.3-cp310-cp310-win_amd64.whl", hash = "sha256:1577735524cdad32f9f694208aa75e422adba74f1baee7551620e43a3141f559"},
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{file = "MarkupSafe-2.1.3-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:ad9e82fb8f09ade1c3e1b996a6337afac2b8b9e365f926f5a61aacc71adc5b3c"},
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{file = "MarkupSafe-2.1.3-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:3c0fae6c3be832a0a0473ac912810b2877c8cb9d76ca48de1ed31e1c68386575"},
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{file = "MarkupSafe-2.1.3-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:b076b6226fb84157e3f7c971a47ff3a679d837cf338547532ab866c57930dbee"},
|
|
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{file = "MarkupSafe-2.1.3.tar.gz", hash = "sha256:af598ed32d6ae86f1b747b82783958b1a4ab8f617b06fe68795c7f026abbdcad"},
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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
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|
[[package]]
|
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|
name = "mpmath"
|
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|
version = "1.3.0"
|
|
|
|
description = "Python library for arbitrary-precision floating-point arithmetic"
|
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optional = false
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|
python-versions = "*"
|
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|
files = [
|
2023-07-04 12:23:55 -06:00
|
|
|
{file = "mpmath-1.3.0-py3-none-any.whl", hash = "sha256:a0b2b9fe80bbcd81a6647ff13108738cfb482d481d826cc0e02f5b35e5c88d2c"},
|
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|
|
{file = "mpmath-1.3.0.tar.gz", hash = "sha256:7a28eb2a9774d00c7bc92411c19a89209d5da7c4c9a9e227be8330a23a25b91f"},
|
|
|
|
]
|
feat(server): Add native support for PEFT Lora models (#762)
- Will detect `peft` model by finding `adapter_config.json`.
- This triggers a totally dedicated `download-weights` path
- This path, loads the adapter config, finds the base model_id
- It loads the base_model
- Then peft_model
- Then `merge_and_unload()`
- Then `save_pretrained(.., safe_serialization=True)
- Add back the config + tokenizer.merge_and_unload()`
- Then `save_pretrained(.., safe_serialization=True)
- Add back the config + tokenizer.
- The chosen location is a **local folder with the name of the user
chosen model id**
PROs:
- Easier than to expect user to merge manually
- Barely any change outside of `download-weights` command.
- This means everything will work in a single load.
- Should enable out of the box SM + HFE
CONs:
- Creates a local merged model in unusual location, potentially
not saved across docker reloads, or ovewriting some files if the PEFT
itself was local and containing other files in addition to the lora
Alternatives considered:
- Add `local_files_only=True` every where (discard because of massive
code change for not a good enough reason)
- Return something to `launcher` about the new model-id (a cleaner
location for this new model), but it would
introduce new communication somewhere where we didn't need it before.
- Using the HF cache folder and *stopping* the flow after
`download-weights` and asking user to restart with the actual local
model location
Fix #482
# What does this PR do?
<!--
Congratulations! You've made it this far! You're not quite done yet
though.
Once merged, your PR is going to appear in the release notes with the
title you set, so make sure it's a great title that fully reflects the
extent of your awesome contribution.
Then, please replace this with a description of the change and which
issue is fixed (if applicable). Please also include relevant motivation
and context. List any dependencies (if any) that are required for this
change.
Once you're done, someone will review your PR shortly (see the section
"Who can review?" below to tag some potential reviewers). They may
suggest changes to make the code even better. If no one reviewed your PR
after a week has passed, don't hesitate to post a new comment
@-mentioning the same persons---sometimes notifications get lost.
-->
<!-- Remove if not applicable -->
Fixes # (issue)
## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the
other checks if that's the case).
- [ ] Did you read the [contributor
guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests),
Pull Request section?
- [ ] Was this discussed/approved via a Github issue or the
[forum](https://discuss.huggingface.co/)? Please add a link
to it if that's the case.
- [ ] Did you make sure to update the documentation with your changes?
Here are the
[documentation
guidelines](https://github.com/huggingface/transformers/tree/main/docs),
and
[here are tips on formatting
docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation).
- [ ] Did you write any new necessary tests?
## Who can review?
Anyone in the community is free to review the PR once the tests have
passed. Feel free to tag
members/contributors who may be interested in your PR.
<!-- Your PR will be replied to 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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|
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|
|
[package.extras]
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|
develop = ["codecov", "pycodestyle", "pytest (>=4.6)", "pytest-cov", "wheel"]
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docs = ["sphinx"]
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|
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gmpy = ["gmpy2 (>=2.1.0a4)"]
|
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tests = ["pytest (>=4.6)"]
|
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|
|
|
|
|
[[package]]
|
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|
name = "multidict"
|
|
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|
version = "6.0.4"
|
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description = "multidict implementation"
|
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|
optional = true
|
|
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|
python-versions = ">=3.7"
|
|
|
|
files = [
|
2023-07-27 06:50:45 -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?
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Fixes # (issue)
## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the
other checks if that's the case).
- [ ] Did you read the [contributor
guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests),
Pull Request section?
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- [ ] Did you make sure to update the documentation with your changes?
Here are the
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- [ ] Did you write any new necessary tests?
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<!-- Your PR will be replied to more quickly if you can figure out the
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2023-08-03 09:22:45 -06:00
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[[package]]
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name = "multiprocess"
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version = "0.70.15"
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description = "better multiprocessing and multithreading in Python"
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optional = true
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python-versions = ">=3.7"
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files = [
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2023-07-27 06:50:45 -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
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[package.dependencies]
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dill = ">=0.3.7"
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[[package]]
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name = "networkx"
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version = "3.1"
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description = "Python package for creating and manipulating graphs and networks"
|
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optional = false
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|
python-versions = ">=3.8"
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files = [
|
2023-07-04 12:23:55 -06:00
|
|
|
{file = "networkx-3.1-py3-none-any.whl", hash = "sha256:4f33f68cb2afcf86f28a45f43efc27a9386b535d567d2127f8f61d51dec58d36"},
|
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|
|
{file = "networkx-3.1.tar.gz", hash = "sha256:de346335408f84de0eada6ff9fafafff9bcda11f0a0dfaa931133debb146ab61"},
|
|
|
|
]
|
feat(server): Add native support for PEFT Lora models (#762)
- Will detect `peft` model by finding `adapter_config.json`.
- This triggers a totally dedicated `download-weights` path
- This path, loads the adapter config, finds the base model_id
- It loads the base_model
- Then peft_model
- Then `merge_and_unload()`
- Then `save_pretrained(.., safe_serialization=True)
- Add back the config + tokenizer.merge_and_unload()`
- Then `save_pretrained(.., safe_serialization=True)
- Add back the config + tokenizer.
- The chosen location is a **local folder with the name of the user
chosen model id**
PROs:
- Easier than to expect user to merge manually
- Barely any change outside of `download-weights` command.
- This means everything will work in a single load.
- Should enable out of the box SM + HFE
CONs:
- Creates a local merged model in unusual location, potentially
not saved across docker reloads, or ovewriting some files if the PEFT
itself was local and containing other files in addition to the lora
Alternatives considered:
- Add `local_files_only=True` every where (discard because of massive
code change for not a good enough reason)
- Return something to `launcher` about the new model-id (a cleaner
location for this new model), but it would
introduce new communication somewhere where we didn't need it before.
- Using the HF cache folder and *stopping* the flow after
`download-weights` and asking user to restart with the actual local
model location
Fix #482
# What does this PR do?
<!--
Congratulations! You've made it this far! You're not quite done yet
though.
Once merged, your PR is going to appear in the release notes with the
title you set, so make sure it's a great title that fully reflects the
extent of your awesome contribution.
Then, please replace this with a description of the change and which
issue is fixed (if applicable). Please also include relevant motivation
and context. List any dependencies (if any) that are required for this
change.
Once you're done, someone will review your PR shortly (see the section
"Who can review?" below to tag some potential reviewers). They may
suggest changes to make the code even better. If no one reviewed your PR
after a week has passed, don't hesitate to post a new comment
@-mentioning the same persons---sometimes notifications get lost.
-->
<!-- Remove if not applicable -->
Fixes # (issue)
## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the
other checks if that's the case).
- [ ] Did you read the [contributor
guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests),
Pull Request section?
- [ ] Was this discussed/approved via a Github issue or the
[forum](https://discuss.huggingface.co/)? Please add a link
to it if that's the case.
- [ ] Did you make sure to update the documentation with your changes?
Here are the
[documentation
guidelines](https://github.com/huggingface/transformers/tree/main/docs),
and
[here are tips on formatting
docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation).
- [ ] Did you write any new necessary tests?
## Who can review?
Anyone in the community is free to review the PR once the tests have
passed. Feel free to tag
members/contributors who may be interested in your PR.
<!-- Your PR will be replied to 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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[package.extras]
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default = ["matplotlib (>=3.4)", "numpy (>=1.20)", "pandas (>=1.3)", "scipy (>=1.8)"]
|
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developer = ["mypy (>=1.1)", "pre-commit (>=3.2)"]
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|
doc = ["nb2plots (>=0.6)", "numpydoc (>=1.5)", "pillow (>=9.4)", "pydata-sphinx-theme (>=0.13)", "sphinx (>=6.1)", "sphinx-gallery (>=0.12)", "texext (>=0.6.7)"]
|
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|
extra = ["lxml (>=4.6)", "pydot (>=1.4.2)", "pygraphviz (>=1.10)", "sympy (>=1.10)"]
|
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test = ["codecov (>=2.1)", "pytest (>=7.2)", "pytest-cov (>=4.0)"]
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[[package]]
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name = "numpy"
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2023-08-03 13:54:39 -06:00
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version = "1.25.2"
|
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 = "Fundamental package for array computing in Python"
|
|
|
|
optional = false
|
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|
|
python-versions = ">=3.9"
|
|
|
|
files = [
|
2023-08-03 13:54:39 -06:00
|
|
|
{file = "numpy-1.25.2-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:db3ccc4e37a6873045580d413fe79b68e47a681af8db2e046f1dacfa11f86eb3"},
|
|
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{file = "numpy-1.25.2-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:90319e4f002795ccfc9050110bbbaa16c944b1c37c0baeea43c5fb881693ae1f"},
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{file = "numpy-1.25.2-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:dfe4a913e29b418d096e696ddd422d8a5d13ffba4ea91f9f60440a3b759b0187"},
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{file = "numpy-1.25.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:f08f2e037bba04e707eebf4bc934f1972a315c883a9e0ebfa8a7756eabf9e357"},
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{file = "numpy-1.25.2-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:bec1e7213c7cb00d67093247f8c4db156fd03075f49876957dca4711306d39c9"},
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{file = "numpy-1.25.2-cp310-cp310-win32.whl", hash = "sha256:7dc869c0c75988e1c693d0e2d5b26034644399dd929bc049db55395b1379e044"},
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{file = "numpy-1.25.2-cp310-cp310-win_amd64.whl", hash = "sha256:834b386f2b8210dca38c71a6e0f4fd6922f7d3fcff935dbe3a570945acb1b545"},
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{file = "numpy-1.25.2-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:c5462d19336db4560041517dbb7759c21d181a67cb01b36ca109b2ae37d32418"},
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{file = "numpy-1.25.2-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:c5652ea24d33585ea39eb6a6a15dac87a1206a692719ff45d53c5282e66d4a8f"},
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{file = "numpy-1.25.2-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:0d60fbae8e0019865fc4784745814cff1c421df5afee233db6d88ab4f14655a2"},
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{file = "numpy-1.25.2-cp311-cp311-win_amd64.whl", hash = "sha256:5c97325a0ba6f9d041feb9390924614b60b99209a71a69c876f71052521d42a4"},
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{file = "numpy-1.25.2-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:eb942bfb6f84df5ce05dbf4b46673ffed0d3da59f13635ea9b926af3deb76926"},
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{file = "numpy-1.25.2-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:8b77775f4b7df768967a7c8b3567e309f617dd5e99aeb886fa14dc1a0791141f"},
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{file = "numpy-1.25.2-cp39-cp39-win32.whl", hash = "sha256:2792d23d62ec51e50ce4d4b7d73de8f67a2fd3ea710dcbc8563a51a03fb07b01"},
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{file = "numpy-1.25.2-cp39-cp39-win_amd64.whl", hash = "sha256:76b4115d42a7dfc5d485d358728cdd8719be33cc5ec6ec08632a5d6fca2ed380"},
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{file = "numpy-1.25.2-pp39-pypy39_pp73-macosx_10_9_x86_64.whl", hash = "sha256:1a1329e26f46230bf77b02cc19e900db9b52f398d6722ca853349a782d4cff55"},
|
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{file = "numpy-1.25.2-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:4c3abc71e8b6edba80a01a52e66d83c5d14433cbcd26a40c329ec7ed09f37901"},
|
|
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{file = "numpy-1.25.2-pp39-pypy39_pp73-win_amd64.whl", hash = "sha256:1b9735c27cea5d995496f46a8b1cd7b408b3f34b6d50459d9ac8fe3a20cc17bf"},
|
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|
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{file = "numpy-1.25.2.tar.gz", hash = "sha256:fd608e19c8d7c55021dffd43bfe5492fab8cc105cc8986f813f8c3c048b38760"},
|
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"
|
|
|
|
version = "1.15.0"
|
|
|
|
description = "OpenTelemetry Python API"
|
|
|
|
optional = false
|
|
|
|
python-versions = ">=3.7"
|
|
|
|
files = [
|
2023-07-04 12:23:55 -06:00
|
|
|
{file = "opentelemetry_api-1.15.0-py3-none-any.whl", hash = "sha256:e6c2d2e42140fd396e96edf75a7ceb11073f4efb4db87565a431cc9d0f93f2e0"},
|
|
|
|
{file = "opentelemetry_api-1.15.0.tar.gz", hash = "sha256:79ab791b4aaad27acc3dc3ba01596db5b5aac2ef75c70622c6038051d6c2cded"},
|
|
|
|
]
|
feat(server): Add native support for PEFT Lora models (#762)
- Will detect `peft` model by finding `adapter_config.json`.
- This triggers a totally dedicated `download-weights` path
- This path, loads the adapter config, finds the base model_id
- It loads the base_model
- Then peft_model
- Then `merge_and_unload()`
- Then `save_pretrained(.., safe_serialization=True)
- Add back the config + tokenizer.merge_and_unload()`
- Then `save_pretrained(.., safe_serialization=True)
- Add back the config + tokenizer.
- The chosen location is a **local folder with the name of the user
chosen model id**
PROs:
- Easier than to expect user to merge manually
- Barely any change outside of `download-weights` command.
- This means everything will work in a single load.
- Should enable out of the box SM + HFE
CONs:
- Creates a local merged model in unusual location, potentially
not saved across docker reloads, or ovewriting some files if the PEFT
itself was local and containing other files in addition to the lora
Alternatives considered:
- Add `local_files_only=True` every where (discard because of massive
code change for not a good enough reason)
- Return something to `launcher` about the new model-id (a cleaner
location for this new model), but it would
introduce new communication somewhere where we didn't need it before.
- Using the HF cache folder and *stopping* the flow after
`download-weights` and asking user to restart with the actual local
model location
Fix #482
# What does this PR do?
<!--
Congratulations! You've made it this far! You're not quite done yet
though.
Once merged, your PR is going to appear in the release notes with the
title you set, so make sure it's a great title that fully reflects the
extent of your awesome contribution.
Then, please replace this with a description of the change and which
issue is fixed (if applicable). Please also include relevant motivation
and context. List any dependencies (if any) that are required for this
change.
Once you're done, someone will review your PR shortly (see the section
"Who can review?" below to tag some potential reviewers). They may
suggest changes to make the code even better. If no one reviewed your PR
after a week has passed, don't hesitate to post a new comment
@-mentioning the same persons---sometimes notifications get lost.
-->
<!-- Remove if not applicable -->
Fixes # (issue)
## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the
other checks if that's the case).
- [ ] Did you read the [contributor
guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests),
Pull Request section?
- [ ] Was this discussed/approved via a Github issue or the
[forum](https://discuss.huggingface.co/)? Please add a link
to it if that's the case.
- [ ] Did you make sure to update the documentation with your changes?
Here are the
[documentation
guidelines](https://github.com/huggingface/transformers/tree/main/docs),
and
[here are tips on formatting
docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation).
- [ ] Did you write any new necessary tests?
## Who can review?
Anyone in the community is free to review the PR once the tests have
passed. Feel free to tag
members/contributors who may be interested in your PR.
<!-- Your PR will be replied to 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"
|
|
|
|
setuptools = ">=16.0"
|
|
|
|
|
|
|
|
[[package]]
|
|
|
|
name = "opentelemetry-exporter-otlp"
|
|
|
|
version = "1.15.0"
|
|
|
|
description = "OpenTelemetry Collector Exporters"
|
|
|
|
optional = false
|
|
|
|
python-versions = ">=3.7"
|
|
|
|
files = [
|
2023-07-04 12:23:55 -06:00
|
|
|
{file = "opentelemetry_exporter_otlp-1.15.0-py3-none-any.whl", hash = "sha256:79f22748b6a54808a0448093dfa189c8490e729f67c134d4c992533d9393b33e"},
|
|
|
|
{file = "opentelemetry_exporter_otlp-1.15.0.tar.gz", hash = "sha256:4f7c49751d9720e2e726e13b0bb958ccade4e29122c305d92c033da432c8d2c5"},
|
|
|
|
]
|
feat(server): Add native support for PEFT Lora models (#762)
- Will detect `peft` model by finding `adapter_config.json`.
- This triggers a totally dedicated `download-weights` path
- This path, loads the adapter config, finds the base model_id
- It loads the base_model
- Then peft_model
- Then `merge_and_unload()`
- Then `save_pretrained(.., safe_serialization=True)
- Add back the config + tokenizer.merge_and_unload()`
- Then `save_pretrained(.., safe_serialization=True)
- Add back the config + tokenizer.
- The chosen location is a **local folder with the name of the user
chosen model id**
PROs:
- Easier than to expect user to merge manually
- Barely any change outside of `download-weights` command.
- This means everything will work in a single load.
- Should enable out of the box SM + HFE
CONs:
- Creates a local merged model in unusual location, potentially
not saved across docker reloads, or ovewriting some files if the PEFT
itself was local and containing other files in addition to the lora
Alternatives considered:
- Add `local_files_only=True` every where (discard because of massive
code change for not a good enough reason)
- Return something to `launcher` about the new model-id (a cleaner
location for this new model), but it would
introduce new communication somewhere where we didn't need it before.
- Using the HF cache folder and *stopping* the flow after
`download-weights` and asking user to restart with the actual local
model location
Fix #482
# What does this PR do?
<!--
Congratulations! You've made it this far! You're not quite done yet
though.
Once merged, your PR is going to appear in the release notes with the
title you set, so make sure it's a great title that fully reflects the
extent of your awesome contribution.
Then, please replace this with a description of the change and which
issue is fixed (if applicable). Please also include relevant motivation
and context. List any dependencies (if any) that are required for this
change.
Once you're done, someone will review your PR shortly (see the section
"Who can review?" below to tag some potential reviewers). They may
suggest changes to make the code even better. If no one reviewed your PR
after a week has passed, don't hesitate to post a new comment
@-mentioning the same persons---sometimes notifications get lost.
-->
<!-- Remove if not applicable -->
Fixes # (issue)
## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the
other checks if that's the case).
- [ ] Did you read the [contributor
guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests),
Pull Request section?
- [ ] Was this discussed/approved via a Github issue or the
[forum](https://discuss.huggingface.co/)? Please add a link
to it if that's the case.
- [ ] Did you make sure to update the documentation with your changes?
Here are the
[documentation
guidelines](https://github.com/huggingface/transformers/tree/main/docs),
and
[here are tips on formatting
docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation).
- [ ] Did you write any new necessary tests?
## Who can review?
Anyone in the community is free to review the PR once the tests have
passed. Feel free to tag
members/contributors who may be interested in your PR.
<!-- Your PR will be replied to 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-exporter-otlp-proto-grpc = "1.15.0"
|
|
|
|
opentelemetry-exporter-otlp-proto-http = "1.15.0"
|
|
|
|
|
|
|
|
[[package]]
|
|
|
|
name = "opentelemetry-exporter-otlp-proto-grpc"
|
|
|
|
version = "1.15.0"
|
|
|
|
description = "OpenTelemetry Collector Protobuf over gRPC Exporter"
|
|
|
|
optional = false
|
|
|
|
python-versions = ">=3.7"
|
|
|
|
files = [
|
2023-07-04 12:23:55 -06:00
|
|
|
{file = "opentelemetry_exporter_otlp_proto_grpc-1.15.0-py3-none-any.whl", hash = "sha256:c2a5492ba7d140109968135d641d06ce3c5bd73c50665f787526065d57d7fd1d"},
|
|
|
|
{file = "opentelemetry_exporter_otlp_proto_grpc-1.15.0.tar.gz", hash = "sha256:844f2a4bb9bcda34e4eb6fe36765e5031aacb36dc60ed88c90fc246942ea26e7"},
|
|
|
|
]
|
feat(server): Add native support for PEFT Lora models (#762)
- Will detect `peft` model by finding `adapter_config.json`.
- This triggers a totally dedicated `download-weights` path
- This path, loads the adapter config, finds the base model_id
- It loads the base_model
- Then peft_model
- Then `merge_and_unload()`
- Then `save_pretrained(.., safe_serialization=True)
- Add back the config + tokenizer.merge_and_unload()`
- Then `save_pretrained(.., safe_serialization=True)
- Add back the config + tokenizer.
- The chosen location is a **local folder with the name of the user
chosen model id**
PROs:
- Easier than to expect user to merge manually
- Barely any change outside of `download-weights` command.
- This means everything will work in a single load.
- Should enable out of the box SM + HFE
CONs:
- Creates a local merged model in unusual location, potentially
not saved across docker reloads, or ovewriting some files if the PEFT
itself was local and containing other files in addition to the lora
Alternatives considered:
- Add `local_files_only=True` every where (discard because of massive
code change for not a good enough reason)
- Return something to `launcher` about the new model-id (a cleaner
location for this new model), but it would
introduce new communication somewhere where we didn't need it before.
- Using the HF cache folder and *stopping* the flow after
`download-weights` and asking user to restart with the actual local
model location
Fix #482
# What does this PR do?
<!--
Congratulations! You've made it this far! You're not quite done yet
though.
Once merged, your PR is going to appear in the release notes with the
title you set, so make sure it's a great title that fully reflects the
extent of your awesome contribution.
Then, please replace this with a description of the change and which
issue is fixed (if applicable). Please also include relevant motivation
and context. List any dependencies (if any) that are required for this
change.
Once you're done, someone will review your PR shortly (see the section
"Who can review?" below to tag some potential reviewers). They may
suggest changes to make the code even better. If no one reviewed your PR
after a week has passed, don't hesitate to post a new comment
@-mentioning the same persons---sometimes notifications get lost.
-->
<!-- Remove if not applicable -->
Fixes # (issue)
## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the
other checks if that's the case).
- [ ] Did you read the [contributor
guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests),
Pull Request section?
- [ ] Was this discussed/approved via a Github issue or the
[forum](https://discuss.huggingface.co/)? Please add a link
to it if that's the case.
- [ ] Did you make sure to update the documentation with your changes?
Here are the
[documentation
guidelines](https://github.com/huggingface/transformers/tree/main/docs),
and
[here are tips on formatting
docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation).
- [ ] Did you write any new necessary tests?
## Who can review?
Anyone in the community is free to review the PR once the tests have
passed. Feel free to tag
members/contributors who may be interested in your PR.
<!-- Your PR will be replied to 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]
|
|
|
|
backoff = {version = ">=1.10.0,<3.0.0", markers = "python_version >= \"3.7\""}
|
|
|
|
googleapis-common-protos = ">=1.52,<2.0"
|
|
|
|
grpcio = ">=1.0.0,<2.0.0"
|
|
|
|
opentelemetry-api = ">=1.12,<2.0"
|
|
|
|
opentelemetry-proto = "1.15.0"
|
|
|
|
opentelemetry-sdk = ">=1.12,<2.0"
|
|
|
|
|
|
|
|
[package.extras]
|
|
|
|
test = ["pytest-grpc"]
|
|
|
|
|
|
|
|
[[package]]
|
|
|
|
name = "opentelemetry-exporter-otlp-proto-http"
|
|
|
|
version = "1.15.0"
|
|
|
|
description = "OpenTelemetry Collector Protobuf over HTTP Exporter"
|
|
|
|
optional = false
|
|
|
|
python-versions = ">=3.7"
|
|
|
|
files = [
|
2023-07-04 12:23:55 -06:00
|
|
|
{file = "opentelemetry_exporter_otlp_proto_http-1.15.0-py3-none-any.whl", hash = "sha256:3ec2a02196c8a54bf5cbf7fe623a5238625638e83b6047a983bdf96e2bbb74c0"},
|
|
|
|
{file = "opentelemetry_exporter_otlp_proto_http-1.15.0.tar.gz", hash = "sha256:11b2c814249a49b22f6cca7a06b05701f561d577b747f3660dfd67b6eb9daf9c"},
|
|
|
|
]
|
feat(server): Add native support for PEFT Lora models (#762)
- Will detect `peft` model by finding `adapter_config.json`.
- This triggers a totally dedicated `download-weights` path
- This path, loads the adapter config, finds the base model_id
- It loads the base_model
- Then peft_model
- Then `merge_and_unload()`
- Then `save_pretrained(.., safe_serialization=True)
- Add back the config + tokenizer.merge_and_unload()`
- Then `save_pretrained(.., safe_serialization=True)
- Add back the config + tokenizer.
- The chosen location is a **local folder with the name of the user
chosen model id**
PROs:
- Easier than to expect user to merge manually
- Barely any change outside of `download-weights` command.
- This means everything will work in a single load.
- Should enable out of the box SM + HFE
CONs:
- Creates a local merged model in unusual location, potentially
not saved across docker reloads, or ovewriting some files if the PEFT
itself was local and containing other files in addition to the lora
Alternatives considered:
- Add `local_files_only=True` every where (discard because of massive
code change for not a good enough reason)
- Return something to `launcher` about the new model-id (a cleaner
location for this new model), but it would
introduce new communication somewhere where we didn't need it before.
- Using the HF cache folder and *stopping* the flow after
`download-weights` and asking user to restart with the actual local
model location
Fix #482
# What does this PR do?
<!--
Congratulations! You've made it this far! You're not quite done yet
though.
Once merged, your PR is going to appear in the release notes with the
title you set, so make sure it's a great title that fully reflects the
extent of your awesome contribution.
Then, please replace this with a description of the change and which
issue is fixed (if applicable). Please also include relevant motivation
and context. List any dependencies (if any) that are required for this
change.
Once you're done, someone will review your PR shortly (see the section
"Who can review?" below to tag some potential reviewers). They may
suggest changes to make the code even better. If no one reviewed your PR
after a week has passed, don't hesitate to post a new comment
@-mentioning the same persons---sometimes notifications get lost.
-->
<!-- Remove if not applicable -->
Fixes # (issue)
## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the
other checks if that's the case).
- [ ] Did you read the [contributor
guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests),
Pull Request section?
- [ ] Was this discussed/approved via a Github issue or the
[forum](https://discuss.huggingface.co/)? Please add a link
to it if that's the case.
- [ ] Did you make sure to update the documentation with your changes?
Here are the
[documentation
guidelines](https://github.com/huggingface/transformers/tree/main/docs),
and
[here are tips on formatting
docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation).
- [ ] Did you write any new necessary tests?
## Who can review?
Anyone in the community is free to review the PR once the tests have
passed. Feel free to tag
members/contributors who may be interested in your PR.
<!-- Your PR will be replied to 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]
|
|
|
|
backoff = {version = ">=1.10.0,<3.0.0", markers = "python_version >= \"3.7\""}
|
|
|
|
googleapis-common-protos = ">=1.52,<2.0"
|
|
|
|
opentelemetry-api = ">=1.12,<2.0"
|
|
|
|
opentelemetry-proto = "1.15.0"
|
|
|
|
opentelemetry-sdk = ">=1.12,<2.0"
|
|
|
|
requests = ">=2.7,<3.0"
|
|
|
|
|
|
|
|
[package.extras]
|
|
|
|
test = ["responses (==0.22.0)"]
|
|
|
|
|
|
|
|
[[package]]
|
|
|
|
name = "opentelemetry-instrumentation"
|
|
|
|
version = "0.36b0"
|
|
|
|
description = "Instrumentation Tools & Auto Instrumentation for OpenTelemetry Python"
|
|
|
|
optional = false
|
|
|
|
python-versions = ">=3.7"
|
|
|
|
files = [
|
2023-07-04 12:23:55 -06:00
|
|
|
{file = "opentelemetry_instrumentation-0.36b0-py3-none-any.whl", hash = "sha256:83ba4ae7d5292b5b33e0f851cc5c76d8f91196b9b3527800fc13855c33383ac2"},
|
|
|
|
{file = "opentelemetry_instrumentation-0.36b0.tar.gz", hash = "sha256:e3ddac9b3b93408ef26c8ecbf38f717042977e16381bb4cd329a5b4cf16998cf"},
|
|
|
|
]
|
feat(server): Add native support for PEFT Lora models (#762)
- Will detect `peft` model by finding `adapter_config.json`.
- This triggers a totally dedicated `download-weights` path
- This path, loads the adapter config, finds the base model_id
- It loads the base_model
- Then peft_model
- Then `merge_and_unload()`
- Then `save_pretrained(.., safe_serialization=True)
- Add back the config + tokenizer.merge_and_unload()`
- Then `save_pretrained(.., safe_serialization=True)
- Add back the config + tokenizer.
- The chosen location is a **local folder with the name of the user
chosen model id**
PROs:
- Easier than to expect user to merge manually
- Barely any change outside of `download-weights` command.
- This means everything will work in a single load.
- Should enable out of the box SM + HFE
CONs:
- Creates a local merged model in unusual location, potentially
not saved across docker reloads, or ovewriting some files if the PEFT
itself was local and containing other files in addition to the lora
Alternatives considered:
- Add `local_files_only=True` every where (discard because of massive
code change for not a good enough reason)
- Return something to `launcher` about the new model-id (a cleaner
location for this new model), but it would
introduce new communication somewhere where we didn't need it before.
- Using the HF cache folder and *stopping* the flow after
`download-weights` and asking user to restart with the actual local
model location
Fix #482
# What does this PR do?
<!--
Congratulations! You've made it this far! You're not quite done yet
though.
Once merged, your PR is going to appear in the release notes with the
title you set, so make sure it's a great title that fully reflects the
extent of your awesome contribution.
Then, please replace this with a description of the change and which
issue is fixed (if applicable). Please also include relevant motivation
and context. List any dependencies (if any) that are required for this
change.
Once you're done, someone will review your PR shortly (see the section
"Who can review?" below to tag some potential reviewers). They may
suggest changes to make the code even better. If no one reviewed your PR
after a week has passed, don't hesitate to post a new comment
@-mentioning the same persons---sometimes notifications get lost.
-->
<!-- Remove if not applicable -->
Fixes # (issue)
## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the
other checks if that's the case).
- [ ] Did you read the [contributor
guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests),
Pull Request section?
- [ ] Was this discussed/approved via a Github issue or the
[forum](https://discuss.huggingface.co/)? Please add a link
to it if that's the case.
- [ ] Did you make sure to update the documentation with your changes?
Here are the
[documentation
guidelines](https://github.com/huggingface/transformers/tree/main/docs),
and
[here are tips on formatting
docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation).
- [ ] Did you write any new necessary tests?
## Who can review?
Anyone in the community is free to review the PR once the tests have
passed. Feel free to tag
members/contributors who may be interested in your PR.
<!-- Your PR will be replied to 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"
|
|
|
|
version = "0.36b0"
|
|
|
|
description = "OpenTelemetry gRPC instrumentation"
|
|
|
|
optional = false
|
|
|
|
python-versions = ">=3.7"
|
|
|
|
files = [
|
2023-07-04 12:23:55 -06:00
|
|
|
{file = "opentelemetry_instrumentation_grpc-0.36b0-py3-none-any.whl", hash = "sha256:eaa246ed2083c97b13bab2555cb9d170e8433230a31476c4cab8a17fa03380a4"},
|
|
|
|
{file = "opentelemetry_instrumentation_grpc-0.36b0.tar.gz", hash = "sha256:dc89447c9eb6ea868970f6c13b4ffdac182cdd5a41dd215a0f5393ca6375be55"},
|
|
|
|
]
|
feat(server): Add native support for PEFT Lora models (#762)
- Will detect `peft` model by finding `adapter_config.json`.
- This triggers a totally dedicated `download-weights` path
- This path, loads the adapter config, finds the base model_id
- It loads the base_model
- Then peft_model
- Then `merge_and_unload()`
- Then `save_pretrained(.., safe_serialization=True)
- Add back the config + tokenizer.merge_and_unload()`
- Then `save_pretrained(.., safe_serialization=True)
- Add back the config + tokenizer.
- The chosen location is a **local folder with the name of the user
chosen model id**
PROs:
- Easier than to expect user to merge manually
- Barely any change outside of `download-weights` command.
- This means everything will work in a single load.
- Should enable out of the box SM + HFE
CONs:
- Creates a local merged model in unusual location, potentially
not saved across docker reloads, or ovewriting some files if the PEFT
itself was local and containing other files in addition to the lora
Alternatives considered:
- Add `local_files_only=True` every where (discard because of massive
code change for not a good enough reason)
- Return something to `launcher` about the new model-id (a cleaner
location for this new model), but it would
introduce new communication somewhere where we didn't need it before.
- Using the HF cache folder and *stopping* the flow after
`download-weights` and asking user to restart with the actual local
model location
Fix #482
# What does this PR do?
<!--
Congratulations! You've made it this far! You're not quite done yet
though.
Once merged, your PR is going to appear in the release notes with the
title you set, so make sure it's a great title that fully reflects the
extent of your awesome contribution.
Then, please replace this with a description of the change and which
issue is fixed (if applicable). Please also include relevant motivation
and context. List any dependencies (if any) that are required for this
change.
Once you're done, someone will review your PR shortly (see the section
"Who can review?" below to tag some potential reviewers). They may
suggest changes to make the code even better. If no one reviewed your PR
after a week has passed, don't hesitate to post a new comment
@-mentioning the same persons---sometimes notifications get lost.
-->
<!-- Remove if not applicable -->
Fixes # (issue)
## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the
other checks if that's the case).
- [ ] Did you read the [contributor
guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests),
Pull Request section?
- [ ] Was this discussed/approved via a Github issue or the
[forum](https://discuss.huggingface.co/)? Please add a link
to it if that's the case.
- [ ] Did you make sure to update the documentation with your changes?
Here are the
[documentation
guidelines](https://github.com/huggingface/transformers/tree/main/docs),
and
[here are tips on formatting
docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation).
- [ ] Did you write any new necessary tests?
## Who can review?
Anyone in the community is free to review the PR once the tests have
passed. Feel free to tag
members/contributors who may be interested in your PR.
<!-- Your PR will be replied to 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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[package.dependencies]
|
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|
|
opentelemetry-api = ">=1.12,<2.0"
|
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|
opentelemetry-instrumentation = "0.36b0"
|
|
|
|
opentelemetry-sdk = ">=1.12,<2.0"
|
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|
|
opentelemetry-semantic-conventions = "0.36b0"
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|
wrapt = ">=1.0.0,<2.0.0"
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[package.extras]
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|
instruments = ["grpcio (>=1.27,<2.0)"]
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|
test = ["opentelemetry-instrumentation-grpc[instruments]", "opentelemetry-sdk (>=1.12,<2.0)", "opentelemetry-test-utils (==0.36b0)", "protobuf (>=3.13,<4.0)"]
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[[package]]
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name = "opentelemetry-proto"
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|
version = "1.15.0"
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|
description = "OpenTelemetry Python Proto"
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optional = false
|
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|
|
python-versions = ">=3.7"
|
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|
|
files = [
|
2023-07-04 12:23:55 -06:00
|
|
|
{file = "opentelemetry_proto-1.15.0-py3-none-any.whl", hash = "sha256:044b6d044b4d10530f250856f933442b8753a17f94ae37c207607f733fb9a844"},
|
|
|
|
{file = "opentelemetry_proto-1.15.0.tar.gz", hash = "sha256:9c4008e40ac8cab359daac283fbe7002c5c29c77ea2674ad5626a249e64e0101"},
|
|
|
|
]
|
feat(server): Add native support for PEFT Lora models (#762)
- Will detect `peft` model by finding `adapter_config.json`.
- This triggers a totally dedicated `download-weights` path
- This path, loads the adapter config, finds the base model_id
- It loads the base_model
- Then peft_model
- Then `merge_and_unload()`
- Then `save_pretrained(.., safe_serialization=True)
- Add back the config + tokenizer.merge_and_unload()`
- Then `save_pretrained(.., safe_serialization=True)
- Add back the config + tokenizer.
- The chosen location is a **local folder with the name of the user
chosen model id**
PROs:
- Easier than to expect user to merge manually
- Barely any change outside of `download-weights` command.
- This means everything will work in a single load.
- Should enable out of the box SM + HFE
CONs:
- Creates a local merged model in unusual location, potentially
not saved across docker reloads, or ovewriting some files if the PEFT
itself was local and containing other files in addition to the lora
Alternatives considered:
- Add `local_files_only=True` every where (discard because of massive
code change for not a good enough reason)
- Return something to `launcher` about the new model-id (a cleaner
location for this new model), but it would
introduce new communication somewhere where we didn't need it before.
- Using the HF cache folder and *stopping* the flow after
`download-weights` and asking user to restart with the actual local
model location
Fix #482
# What does this PR do?
<!--
Congratulations! You've made it this far! You're not quite done yet
though.
Once merged, your PR is going to appear in the release notes with the
title you set, so make sure it's a great title that fully reflects the
extent of your awesome contribution.
Then, please replace this with a description of the change and which
issue is fixed (if applicable). Please also include relevant motivation
and context. List any dependencies (if any) that are required for this
change.
Once you're done, someone will review your PR shortly (see the section
"Who can review?" below to tag some potential reviewers). They may
suggest changes to make the code even better. If no one reviewed your PR
after a week has passed, don't hesitate to post a new comment
@-mentioning the same persons---sometimes notifications get lost.
-->
<!-- Remove if not applicable -->
Fixes # (issue)
## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the
other checks if that's the case).
- [ ] Did you read the [contributor
guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests),
Pull Request section?
- [ ] Was this discussed/approved via a Github issue or the
[forum](https://discuss.huggingface.co/)? Please add a link
to it if that's the case.
- [ ] Did you make sure to update the documentation with your changes?
Here are the
[documentation
guidelines](https://github.com/huggingface/transformers/tree/main/docs),
and
[here are tips on formatting
docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation).
- [ ] Did you write any new necessary tests?
## Who can review?
Anyone in the community is free to review the PR once the tests have
passed. Feel free to tag
members/contributors who may be interested in your PR.
<!-- Your PR will be replied to 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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|
|
|
|
[package.dependencies]
|
|
|
|
protobuf = ">=3.19,<5.0"
|
|
|
|
|
|
|
|
[[package]]
|
|
|
|
name = "opentelemetry-sdk"
|
|
|
|
version = "1.15.0"
|
|
|
|
description = "OpenTelemetry Python SDK"
|
|
|
|
optional = false
|
|
|
|
python-versions = ">=3.7"
|
|
|
|
files = [
|
2023-07-04 12:23:55 -06:00
|
|
|
{file = "opentelemetry_sdk-1.15.0-py3-none-any.whl", hash = "sha256:555c533e9837766119bbccc7a80458c9971d853a6f1da683a2246cd5e53b4645"},
|
|
|
|
{file = "opentelemetry_sdk-1.15.0.tar.gz", hash = "sha256:98dbffcfeebcbff12c0c974292d6ea603180a145904cf838b1fe4d5c99078425"},
|
|
|
|
]
|
feat(server): Add native support for PEFT Lora models (#762)
- Will detect `peft` model by finding `adapter_config.json`.
- This triggers a totally dedicated `download-weights` path
- This path, loads the adapter config, finds the base model_id
- It loads the base_model
- Then peft_model
- Then `merge_and_unload()`
- Then `save_pretrained(.., safe_serialization=True)
- Add back the config + tokenizer.merge_and_unload()`
- Then `save_pretrained(.., safe_serialization=True)
- Add back the config + tokenizer.
- The chosen location is a **local folder with the name of the user
chosen model id**
PROs:
- Easier than to expect user to merge manually
- Barely any change outside of `download-weights` command.
- This means everything will work in a single load.
- Should enable out of the box SM + HFE
CONs:
- Creates a local merged model in unusual location, potentially
not saved across docker reloads, or ovewriting some files if the PEFT
itself was local and containing other files in addition to the lora
Alternatives considered:
- Add `local_files_only=True` every where (discard because of massive
code change for not a good enough reason)
- Return something to `launcher` about the new model-id (a cleaner
location for this new model), but it would
introduce new communication somewhere where we didn't need it before.
- Using the HF cache folder and *stopping* the flow after
`download-weights` and asking user to restart with the actual local
model location
Fix #482
# What does this PR do?
<!--
Congratulations! You've made it this far! You're not quite done yet
though.
Once merged, your PR is going to appear in the release notes with the
title you set, so make sure it's a great title that fully reflects the
extent of your awesome contribution.
Then, please replace this with a description of the change and which
issue is fixed (if applicable). Please also include relevant motivation
and context. List any dependencies (if any) that are required for this
change.
Once you're done, someone will review your PR shortly (see the section
"Who can review?" below to tag some potential reviewers). They may
suggest changes to make the code even better. If no one reviewed your PR
after a week has passed, don't hesitate to post a new comment
@-mentioning the same persons---sometimes notifications get lost.
-->
<!-- Remove if not applicable -->
Fixes # (issue)
## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the
other checks if that's the case).
- [ ] Did you read the [contributor
guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests),
Pull Request section?
- [ ] Was this discussed/approved via a Github issue or the
[forum](https://discuss.huggingface.co/)? Please add a link
to it if that's the case.
- [ ] Did you make sure to update the documentation with your changes?
Here are the
[documentation
guidelines](https://github.com/huggingface/transformers/tree/main/docs),
and
[here are tips on formatting
docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation).
- [ ] Did you write any new necessary tests?
## Who can review?
Anyone in the community is free to review the PR once the tests have
passed. Feel free to tag
members/contributors who may be interested in your PR.
<!-- Your PR will be replied to 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 = "1.15.0"
|
|
|
|
opentelemetry-semantic-conventions = "0.36b0"
|
|
|
|
setuptools = ">=16.0"
|
|
|
|
typing-extensions = ">=3.7.4"
|
|
|
|
|
|
|
|
[[package]]
|
|
|
|
name = "opentelemetry-semantic-conventions"
|
|
|
|
version = "0.36b0"
|
|
|
|
description = "OpenTelemetry Semantic Conventions"
|
|
|
|
optional = false
|
|
|
|
python-versions = ">=3.7"
|
|
|
|
files = [
|
2023-07-04 12:23:55 -06:00
|
|
|
{file = "opentelemetry_semantic_conventions-0.36b0-py3-none-any.whl", hash = "sha256:adc05635e87b9d3e007c9f530eed487fc3ef2177d02f82f674f28ebf9aff8243"},
|
|
|
|
{file = "opentelemetry_semantic_conventions-0.36b0.tar.gz", hash = "sha256:829dc221795467d98b773c04096e29be038d77526dc8d6ac76f546fb6279bf01"},
|
|
|
|
]
|
feat(server): Add native support for PEFT Lora models (#762)
- Will detect `peft` model by finding `adapter_config.json`.
- This triggers a totally dedicated `download-weights` path
- This path, loads the adapter config, finds the base model_id
- It loads the base_model
- Then peft_model
- Then `merge_and_unload()`
- Then `save_pretrained(.., safe_serialization=True)
- Add back the config + tokenizer.merge_and_unload()`
- Then `save_pretrained(.., safe_serialization=True)
- Add back the config + tokenizer.
- The chosen location is a **local folder with the name of the user
chosen model id**
PROs:
- Easier than to expect user to merge manually
- Barely any change outside of `download-weights` command.
- This means everything will work in a single load.
- Should enable out of the box SM + HFE
CONs:
- Creates a local merged model in unusual location, potentially
not saved across docker reloads, or ovewriting some files if the PEFT
itself was local and containing other files in addition to the lora
Alternatives considered:
- Add `local_files_only=True` every where (discard because of massive
code change for not a good enough reason)
- Return something to `launcher` about the new model-id (a cleaner
location for this new model), but it would
introduce new communication somewhere where we didn't need it before.
- Using the HF cache folder and *stopping* the flow after
`download-weights` and asking user to restart with the actual local
model location
Fix #482
# What does this PR do?
<!--
Congratulations! You've made it this far! You're not quite done yet
though.
Once merged, your PR is going to appear in the release notes with the
title you set, so make sure it's a great title that fully reflects the
extent of your awesome contribution.
Then, please replace this with a description of the change and which
issue is fixed (if applicable). Please also include relevant motivation
and context. List any dependencies (if any) that are required for this
change.
Once you're done, someone will review your PR shortly (see the section
"Who can review?" below to tag some potential reviewers). They may
suggest changes to make the code even better. If no one reviewed your PR
after a week has passed, don't hesitate to post a new comment
@-mentioning the same persons---sometimes notifications get lost.
-->
<!-- Remove if not applicable -->
Fixes # (issue)
## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the
other checks if that's the case).
- [ ] Did you read the [contributor
guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests),
Pull Request section?
- [ ] Was this discussed/approved via a Github issue or the
[forum](https://discuss.huggingface.co/)? Please add a link
to it if that's the case.
- [ ] Did you make sure to update the documentation with your changes?
Here are the
[documentation
guidelines](https://github.com/huggingface/transformers/tree/main/docs),
and
[here are tips on formatting
docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation).
- [ ] Did you write any new necessary tests?
## Who can review?
Anyone in the community is free to review the PR once the tests have
passed. Feel free to tag
members/contributors who may be interested in your PR.
<!-- Your PR will be replied to 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"
|
|
|
|
version = "23.1"
|
|
|
|
description = "Core utilities for Python packages"
|
|
|
|
optional = false
|
|
|
|
python-versions = ">=3.7"
|
|
|
|
files = [
|
2023-07-04 12:23:55 -06:00
|
|
|
{file = "packaging-23.1-py3-none-any.whl", hash = "sha256:994793af429502c4ea2ebf6bf664629d07c1a9fe974af92966e4b8d2df7edc61"},
|
|
|
|
{file = "packaging-23.1.tar.gz", hash = "sha256:a392980d2b6cffa644431898be54b0045151319d1e7ec34f0cfed48767dd334f"},
|
|
|
|
]
|
feat(server): Add native support for PEFT Lora models (#762)
- Will detect `peft` model by finding `adapter_config.json`.
- This triggers a totally dedicated `download-weights` path
- This path, loads the adapter config, finds the base model_id
- It loads the base_model
- Then peft_model
- Then `merge_and_unload()`
- Then `save_pretrained(.., safe_serialization=True)
- Add back the config + tokenizer.merge_and_unload()`
- Then `save_pretrained(.., safe_serialization=True)
- Add back the config + tokenizer.
- The chosen location is a **local folder with the name of the user
chosen model id**
PROs:
- Easier than to expect user to merge manually
- Barely any change outside of `download-weights` command.
- This means everything will work in a single load.
- Should enable out of the box SM + HFE
CONs:
- Creates a local merged model in unusual location, potentially
not saved across docker reloads, or ovewriting some files if the PEFT
itself was local and containing other files in addition to the lora
Alternatives considered:
- Add `local_files_only=True` every where (discard because of massive
code change for not a good enough reason)
- Return something to `launcher` about the new model-id (a cleaner
location for this new model), but it would
introduce new communication somewhere where we didn't need it before.
- Using the HF cache folder and *stopping* the flow after
`download-weights` and asking user to restart with the actual local
model location
Fix #482
# What does this PR do?
<!--
Congratulations! You've made it this far! You're not quite done yet
though.
Once merged, your PR is going to appear in the release notes with the
title you set, so make sure it's a great title that fully reflects the
extent of your awesome contribution.
Then, please replace this with a description of the change and which
issue is fixed (if applicable). Please also include relevant motivation
and context. List any dependencies (if any) that are required for this
change.
Once you're done, someone will review your PR shortly (see the section
"Who can review?" below to tag some potential reviewers). They may
suggest changes to make the code even better. If no one reviewed your PR
after a week has passed, don't hesitate to post a new comment
@-mentioning the same persons---sometimes notifications get lost.
-->
<!-- Remove if not applicable -->
Fixes # (issue)
## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the
other checks if that's the case).
- [ ] Did you read the [contributor
guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests),
Pull Request section?
- [ ] Was this discussed/approved via a Github issue or the
[forum](https://discuss.huggingface.co/)? Please add a link
to it if that's the case.
- [ ] Did you make sure to update the documentation with your changes?
Here are the
[documentation
guidelines](https://github.com/huggingface/transformers/tree/main/docs),
and
[here are tips on formatting
docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation).
- [ ] Did you write any new necessary tests?
## Who can review?
Anyone in the community is free to review the PR once the tests have
passed. Feel free to tag
members/contributors who may be interested in your PR.
<!-- Your PR will be replied to 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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|
|
|
|
|
[[package]]
|
|
|
|
name = "pandas"
|
|
|
|
version = "2.0.3"
|
|
|
|
description = "Powerful data structures for data analysis, time series, and statistics"
|
|
|
|
optional = true
|
|
|
|
python-versions = ">=3.8"
|
|
|
|
files = [
|
2023-07-27 06:50:45 -06:00
|
|
|
{file = "pandas-2.0.3-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:e4c7c9f27a4185304c7caf96dc7d91bc60bc162221152de697c98eb0b2648dd8"},
|
|
|
|
{file = "pandas-2.0.3-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:f167beed68918d62bffb6ec64f2e1d8a7d297a038f86d4aed056b9493fca407f"},
|
|
|
|
{file = "pandas-2.0.3-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:ce0c6f76a0f1ba361551f3e6dceaff06bde7514a374aa43e33b588ec10420183"},
|
|
|
|
{file = "pandas-2.0.3-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:ba619e410a21d8c387a1ea6e8a0e49bb42216474436245718d7f2e88a2f8d7c0"},
|
|
|
|
{file = "pandas-2.0.3-cp310-cp310-win32.whl", hash = "sha256:3ef285093b4fe5058eefd756100a367f27029913760773c8bf1d2d8bebe5d210"},
|
|
|
|
{file = "pandas-2.0.3-cp310-cp310-win_amd64.whl", hash = "sha256:9ee1a69328d5c36c98d8e74db06f4ad518a1840e8ccb94a4ba86920986bb617e"},
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{file = "pandas-2.0.3-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:b084b91d8d66ab19f5bb3256cbd5ea661848338301940e17f4492b2ce0801fe8"},
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{file = "pandas-2.0.3-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:37673e3bdf1551b95bf5d4ce372b37770f9529743d2498032439371fc7b7eb26"},
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{file = "pandas-2.0.3-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:b9cb1e14fdb546396b7e1b923ffaeeac24e4cedd14266c3497216dd4448e4f2d"},
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{file = "pandas-2.0.3-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:d9cd88488cceb7635aebb84809d087468eb33551097d600c6dad13602029c2df"},
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{file = "pandas-2.0.3-cp311-cp311-win32.whl", hash = "sha256:694888a81198786f0e164ee3a581df7d505024fbb1f15202fc7db88a71d84ebd"},
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{file = "pandas-2.0.3-cp311-cp311-win_amd64.whl", hash = "sha256:6a21ab5c89dcbd57f78d0ae16630b090eec626360085a4148693def5452d8a6b"},
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{file = "pandas-2.0.3-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:9e4da0d45e7f34c069fe4d522359df7d23badf83abc1d1cef398895822d11061"},
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{file = "pandas-2.0.3-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:32fca2ee1b0d93dd71d979726b12b61faa06aeb93cf77468776287f41ff8fdc5"},
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{file = "pandas-2.0.3-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:258d3624b3ae734490e4d63c430256e716f488c4fcb7c8e9bde2d3aa46c29089"},
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{file = "pandas-2.0.3-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:9eae3dc34fa1aa7772dd3fc60270d13ced7346fcbcfee017d3132ec625e23bb0"},
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{file = "pandas-2.0.3-cp38-cp38-win32.whl", hash = "sha256:f3421a7afb1a43f7e38e82e844e2bca9a6d793d66c1a7f9f0ff39a795bbc5e02"},
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{file = "pandas-2.0.3-cp38-cp38-win_amd64.whl", hash = "sha256:69d7f3884c95da3a31ef82b7618af5710dba95bb885ffab339aad925c3e8ce78"},
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{file = "pandas-2.0.3-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:5247fb1ba347c1261cbbf0fcfba4a3121fbb4029d95d9ef4dc45406620b25c8b"},
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{file = "pandas-2.0.3-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:81af086f4543c9d8bb128328b5d32e9986e0c84d3ee673a2ac6fb57fd14f755e"},
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{file = "pandas-2.0.3.tar.gz", hash = "sha256:c02f372a88e0d17f36d3093a644c73cfc1788e876a7c4bcb4020a77512e2043c"},
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]
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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?
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Fixes # (issue)
## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the
other checks if that's the case).
- [ ] Did you read the [contributor
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to it if that's the case.
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Here are the
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and
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- [ ] Did you write any new necessary tests?
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<!-- Your PR will be replied to more quickly if you can figure out the
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2023-08-03 09:22:45 -06:00
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[package.dependencies]
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numpy = [
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{version = ">=1.20.3", markers = "python_version < \"3.10\""},
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{version = ">=1.21.0", markers = "python_version >= \"3.10\""},
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{version = ">=1.23.2", markers = "python_version >= \"3.11\""},
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]
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python-dateutil = ">=2.8.2"
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pytz = ">=2020.1"
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tzdata = ">=2022.1"
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[package.extras]
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all = ["PyQt5 (>=5.15.1)", "SQLAlchemy (>=1.4.16)", "beautifulsoup4 (>=4.9.3)", "bottleneck (>=1.3.2)", "brotlipy (>=0.7.0)", "fastparquet (>=0.6.3)", "fsspec (>=2021.07.0)", "gcsfs (>=2021.07.0)", "html5lib (>=1.1)", "hypothesis (>=6.34.2)", "jinja2 (>=3.0.0)", "lxml (>=4.6.3)", "matplotlib (>=3.6.1)", "numba (>=0.53.1)", "numexpr (>=2.7.3)", "odfpy (>=1.4.1)", "openpyxl (>=3.0.7)", "pandas-gbq (>=0.15.0)", "psycopg2 (>=2.8.6)", "pyarrow (>=7.0.0)", "pymysql (>=1.0.2)", "pyreadstat (>=1.1.2)", "pytest (>=7.3.2)", "pytest-asyncio (>=0.17.0)", "pytest-xdist (>=2.2.0)", "python-snappy (>=0.6.0)", "pyxlsb (>=1.0.8)", "qtpy (>=2.2.0)", "s3fs (>=2021.08.0)", "scipy (>=1.7.1)", "tables (>=3.6.1)", "tabulate (>=0.8.9)", "xarray (>=0.21.0)", "xlrd (>=2.0.1)", "xlsxwriter (>=1.4.3)", "zstandard (>=0.15.2)"]
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aws = ["s3fs (>=2021.08.0)"]
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clipboard = ["PyQt5 (>=5.15.1)", "qtpy (>=2.2.0)"]
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compression = ["brotlipy (>=0.7.0)", "python-snappy (>=0.6.0)", "zstandard (>=0.15.2)"]
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computation = ["scipy (>=1.7.1)", "xarray (>=0.21.0)"]
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excel = ["odfpy (>=1.4.1)", "openpyxl (>=3.0.7)", "pyxlsb (>=1.0.8)", "xlrd (>=2.0.1)", "xlsxwriter (>=1.4.3)"]
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feather = ["pyarrow (>=7.0.0)"]
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fss = ["fsspec (>=2021.07.0)"]
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gcp = ["gcsfs (>=2021.07.0)", "pandas-gbq (>=0.15.0)"]
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hdf5 = ["tables (>=3.6.1)"]
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html = ["beautifulsoup4 (>=4.9.3)", "html5lib (>=1.1)", "lxml (>=4.6.3)"]
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mysql = ["SQLAlchemy (>=1.4.16)", "pymysql (>=1.0.2)"]
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output-formatting = ["jinja2 (>=3.0.0)", "tabulate (>=0.8.9)"]
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parquet = ["pyarrow (>=7.0.0)"]
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performance = ["bottleneck (>=1.3.2)", "numba (>=0.53.1)", "numexpr (>=2.7.1)"]
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plot = ["matplotlib (>=3.6.1)"]
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postgresql = ["SQLAlchemy (>=1.4.16)", "psycopg2 (>=2.8.6)"]
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spss = ["pyreadstat (>=1.1.2)"]
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sql-other = ["SQLAlchemy (>=1.4.16)"]
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test = ["hypothesis (>=6.34.2)", "pytest (>=7.3.2)", "pytest-asyncio (>=0.17.0)", "pytest-xdist (>=2.2.0)"]
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xml = ["lxml (>=4.6.3)"]
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[[package]]
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name = "peft"
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version = "0.4.0"
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description = "Parameter-Efficient Fine-Tuning (PEFT)"
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optional = false
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python-versions = ">=3.8.0"
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files = [
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{file = "peft-0.4.0-py3-none-any.whl", hash = "sha256:2cf992772a6d703814477e0bdcdadd68cb8ea388111ce2d793dd2ff0e438f357"},
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{file = "peft-0.4.0.tar.gz", hash = "sha256:e768fa22d6e9f32aa7e891f0d06f355960278ca4dc0cdd96bff71f6f06269207"},
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]
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[package.dependencies]
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accelerate = "*"
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numpy = ">=1.17"
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packaging = ">=20.0"
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psutil = "*"
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pyyaml = "*"
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safetensors = "*"
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torch = ">=1.13.0"
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transformers = "*"
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[package.extras]
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dev = ["black (>=22.0,<23.0)", "hf-doc-builder", "ruff (>=0.0.241)", "urllib3 (<=2.0.0)"]
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docs-specific = ["hf-doc-builder"]
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quality = ["black (>=22.0,<23.0)", "ruff (>=0.0.241)", "urllib3 (<=2.0.0)"]
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test = ["black (>=22.0,<23.0)", "datasets", "diffusers", "hf-doc-builder", "parameterized", "pytest", "pytest-cov", "pytest-xdist", "ruff (>=0.0.241)", "urllib3 (<=2.0.0)"]
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2023-08-17 06:38:49 -06:00
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[[package]]
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name = "pillow"
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version = "10.0.0"
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description = "Python Imaging Library (Fork)"
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optional = false
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python-versions = ">=3.8"
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files = [
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{file = "Pillow-10.0.0-cp39-cp39-manylinux_2_28_x86_64.whl", hash = "sha256:368ab3dfb5f49e312231b6f27b8820c823652b7cd29cfbd34090565a015e99ba"},
|
|
|
|
{file = "Pillow-10.0.0-cp39-cp39-musllinux_1_1_aarch64.whl", hash = "sha256:608bfdee0d57cf297d32bcbb3c728dc1da0907519d1784962c5f0c68bb93e5a3"},
|
|
|
|
{file = "Pillow-10.0.0-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:5c6e3df6bdd396749bafd45314871b3d0af81ff935b2d188385e970052091017"},
|
|
|
|
{file = "Pillow-10.0.0-cp39-cp39-win_amd64.whl", hash = "sha256:7be600823e4c8631b74e4a0d38384c73f680e6105a7d3c6824fcf226c178c7e6"},
|
|
|
|
{file = "Pillow-10.0.0-pp310-pypy310_pp73-macosx_10_10_x86_64.whl", hash = "sha256:92be919bbc9f7d09f7ae343c38f5bb21c973d2576c1d45600fce4b74bafa7ac0"},
|
|
|
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{file = "Pillow-10.0.0-pp310-pypy310_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:8f8182b523b2289f7c415f589118228d30ac8c355baa2f3194ced084dac2dbba"},
|
|
|
|
{file = "Pillow-10.0.0-pp310-pypy310_pp73-manylinux_2_28_x86_64.whl", hash = "sha256:38250a349b6b390ee6047a62c086d3817ac69022c127f8a5dc058c31ccef17f3"},
|
|
|
|
{file = "Pillow-10.0.0-pp310-pypy310_pp73-win_amd64.whl", hash = "sha256:88af2003543cc40c80f6fca01411892ec52b11021b3dc22ec3bc9d5afd1c5334"},
|
|
|
|
{file = "Pillow-10.0.0-pp39-pypy39_pp73-macosx_10_10_x86_64.whl", hash = "sha256:c189af0545965fa8d3b9613cfdb0cd37f9d71349e0f7750e1fd704648d475ed2"},
|
|
|
|
{file = "Pillow-10.0.0-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:ce7b031a6fc11365970e6a5686d7ba8c63e4c1cf1ea143811acbb524295eabed"},
|
|
|
|
{file = "Pillow-10.0.0-pp39-pypy39_pp73-manylinux_2_28_x86_64.whl", hash = "sha256:db24668940f82321e746773a4bc617bfac06ec831e5c88b643f91f122a785684"},
|
|
|
|
{file = "Pillow-10.0.0-pp39-pypy39_pp73-win_amd64.whl", hash = "sha256:efe8c0681042536e0d06c11f48cebe759707c9e9abf880ee213541c5b46c5bf3"},
|
|
|
|
{file = "Pillow-10.0.0.tar.gz", hash = "sha256:9c82b5b3e043c7af0d95792d0d20ccf68f61a1fec6b3530e718b688422727396"},
|
|
|
|
]
|
|
|
|
|
|
|
|
[package.extras]
|
|
|
|
docs = ["furo", "olefile", "sphinx (>=2.4)", "sphinx-copybutton", "sphinx-inline-tabs", "sphinx-removed-in", "sphinxext-opengraph"]
|
|
|
|
tests = ["check-manifest", "coverage", "defusedxml", "markdown2", "olefile", "packaging", "pyroma", "pytest", "pytest-cov", "pytest-timeout"]
|
|
|
|
|
feat(server): Add native support for PEFT Lora models (#762)
- Will detect `peft` model by finding `adapter_config.json`.
- This triggers a totally dedicated `download-weights` path
- This path, loads the adapter config, finds the base model_id
- It loads the base_model
- Then peft_model
- Then `merge_and_unload()`
- Then `save_pretrained(.., safe_serialization=True)
- Add back the config + tokenizer.merge_and_unload()`
- Then `save_pretrained(.., safe_serialization=True)
- Add back the config + tokenizer.
- The chosen location is a **local folder with the name of the user
chosen model id**
PROs:
- Easier than to expect user to merge manually
- Barely any change outside of `download-weights` command.
- This means everything will work in a single load.
- Should enable out of the box SM + HFE
CONs:
- Creates a local merged model in unusual location, potentially
not saved across docker reloads, or ovewriting some files if the PEFT
itself was local and containing other files in addition to the lora
Alternatives considered:
- Add `local_files_only=True` every where (discard because of massive
code change for not a good enough reason)
- Return something to `launcher` about the new model-id (a cleaner
location for this new model), but it would
introduce new communication somewhere where we didn't need it before.
- Using the HF cache folder and *stopping* the flow after
`download-weights` and asking user to restart with the actual local
model location
Fix #482
# What does this PR do?
<!--
Congratulations! You've made it this far! You're not quite done yet
though.
Once merged, your PR is going to appear in the release notes with the
title you set, so make sure it's a great title that fully reflects the
extent of your awesome contribution.
Then, please replace this with a description of the change and which
issue is fixed (if applicable). Please also include relevant motivation
and context. List any dependencies (if any) that are required for this
change.
Once you're done, someone will review your PR shortly (see the section
"Who can review?" below to tag some potential reviewers). They may
suggest changes to make the code even better. If no one reviewed your PR
after a week has passed, don't hesitate to post a new comment
@-mentioning the same persons---sometimes notifications get lost.
-->
<!-- Remove if not applicable -->
Fixes # (issue)
## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the
other checks if that's the case).
- [ ] Did you read the [contributor
guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests),
Pull Request section?
- [ ] Was this discussed/approved via a Github issue or the
[forum](https://discuss.huggingface.co/)? Please add a link
to it if that's the case.
- [ ] Did you make sure to update the documentation with your changes?
Here are the
[documentation
guidelines](https://github.com/huggingface/transformers/tree/main/docs),
and
[here are tips on formatting
docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation).
- [ ] Did you write any new necessary tests?
## Who can review?
Anyone in the community is free to review the PR once the tests have
passed. Feel free to tag
members/contributors who may be interested in your PR.
<!-- Your PR will be replied to 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"
|
2023-08-29 06:28:22 -06:00
|
|
|
version = "1.3.0"
|
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
|
|
|
description = "plugin and hook calling mechanisms for python"
|
|
|
|
optional = false
|
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 = [
|
2023-08-29 06:28:22 -06:00
|
|
|
{file = "pluggy-1.3.0-py3-none-any.whl", hash = "sha256:d89c696a773f8bd377d18e5ecda92b7a3793cbe66c87060a6fb58c7b6e1061f7"},
|
|
|
|
{file = "pluggy-1.3.0.tar.gz", hash = "sha256:cf61ae8f126ac6f7c451172cf30e3e43d3ca77615509771b3a984a0730651e12"},
|
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"]
|
|
|
|
|
|
|
|
[[package]]
|
|
|
|
name = "protobuf"
|
2023-08-29 06:28:22 -06:00
|
|
|
version = "4.24.2"
|
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 = ""
|
|
|
|
optional = false
|
|
|
|
python-versions = ">=3.7"
|
|
|
|
files = [
|
2023-08-29 06:28:22 -06:00
|
|
|
{file = "protobuf-4.24.2-cp310-abi3-win32.whl", hash = "sha256:58e12d2c1aa428ece2281cef09bbaa6938b083bcda606db3da4e02e991a0d924"},
|
|
|
|
{file = "protobuf-4.24.2-cp310-abi3-win_amd64.whl", hash = "sha256:77700b55ba41144fc64828e02afb41901b42497b8217b558e4a001f18a85f2e3"},
|
|
|
|
{file = "protobuf-4.24.2-cp37-abi3-macosx_10_9_universal2.whl", hash = "sha256:237b9a50bd3b7307d0d834c1b0eb1a6cd47d3f4c2da840802cd03ea288ae8880"},
|
|
|
|
{file = "protobuf-4.24.2-cp37-abi3-manylinux2014_aarch64.whl", hash = "sha256:25ae91d21e3ce8d874211110c2f7edd6384816fb44e06b2867afe35139e1fd1c"},
|
|
|
|
{file = "protobuf-4.24.2-cp37-abi3-manylinux2014_x86_64.whl", hash = "sha256:c00c3c7eb9ad3833806e21e86dca448f46035242a680f81c3fe068ff65e79c74"},
|
|
|
|
{file = "protobuf-4.24.2-cp37-cp37m-win32.whl", hash = "sha256:4e69965e7e54de4db989289a9b971a099e626f6167a9351e9d112221fc691bc1"},
|
|
|
|
{file = "protobuf-4.24.2-cp37-cp37m-win_amd64.whl", hash = "sha256:c5cdd486af081bf752225b26809d2d0a85e575b80a84cde5172a05bbb1990099"},
|
|
|
|
{file = "protobuf-4.24.2-cp38-cp38-win32.whl", hash = "sha256:6bd26c1fa9038b26c5c044ee77e0ecb18463e957fefbaeb81a3feb419313a54e"},
|
|
|
|
{file = "protobuf-4.24.2-cp38-cp38-win_amd64.whl", hash = "sha256:bb7aa97c252279da65584af0456f802bd4b2de429eb945bbc9b3d61a42a8cd16"},
|
|
|
|
{file = "protobuf-4.24.2-cp39-cp39-win32.whl", hash = "sha256:2b23bd6e06445699b12f525f3e92a916f2dcf45ffba441026357dea7fa46f42b"},
|
|
|
|
{file = "protobuf-4.24.2-cp39-cp39-win_amd64.whl", hash = "sha256:839952e759fc40b5d46be319a265cf94920174d88de31657d5622b5d8d6be5cd"},
|
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|
{file = "protobuf-4.24.2-py3-none-any.whl", hash = "sha256:3b7b170d3491ceed33f723bbf2d5a260f8a4e23843799a3906f16ef736ef251e"},
|
|
|
|
{file = "protobuf-4.24.2.tar.gz", hash = "sha256:7fda70797ddec31ddfa3576cbdcc3ddbb6b3078b737a1a87ab9136af0570cd6e"},
|
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
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[[package]]
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name = "psutil"
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version = "5.9.5"
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description = "Cross-platform lib for process and system monitoring in Python."
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optional = false
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python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
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files = [
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2023-07-04 12:23:55 -06:00
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{file = "psutil-5.9.5-cp27-cp27m-macosx_10_9_x86_64.whl", hash = "sha256:be8929ce4313f9f8146caad4272f6abb8bf99fc6cf59344a3167ecd74f4f203f"},
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{file = "psutil-5.9.5-cp27-cp27m-manylinux2010_i686.whl", hash = "sha256:ab8ed1a1d77c95453db1ae00a3f9c50227ebd955437bcf2a574ba8adbf6a74d5"},
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{file = "psutil-5.9.5-cp27-none-win32.whl", hash = "sha256:5b9b8cb93f507e8dbaf22af6a2fd0ccbe8244bf30b1baad6b3954e935157ae3f"},
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{file = "psutil-5.9.5-cp27-none-win_amd64.whl", hash = "sha256:8c5f7c5a052d1d567db4ddd231a9d27a74e8e4a9c3f44b1032762bd7b9fdcd42"},
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{file = "psutil-5.9.5-cp36-abi3-macosx_10_9_x86_64.whl", hash = "sha256:3c6f686f4225553615612f6d9bc21f1c0e305f75d7d8454f9b46e901778e7217"},
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{file = "psutil-5.9.5-cp36-abi3-manylinux_2_12_i686.manylinux2010_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:7a7dd9997128a0d928ed4fb2c2d57e5102bb6089027939f3b722f3a210f9a8da"},
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{file = "psutil-5.9.5-cp36-abi3-manylinux_2_12_x86_64.manylinux2010_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:89518112647f1276b03ca97b65cc7f64ca587b1eb0278383017c2a0dcc26cbe4"},
|
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
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|
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{file = "psutil-5.9.5-cp36-abi3-win32.whl", hash = "sha256:104a5cc0e31baa2bcf67900be36acde157756b9c44017b86b2c049f11957887d"},
|
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{file = "psutil-5.9.5-cp36-abi3-win_amd64.whl", hash = "sha256:b258c0c1c9d145a1d5ceffab1134441c4c5113b2417fafff7315a917a026c3c9"},
|
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|
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{file = "psutil-5.9.5-cp38-abi3-macosx_11_0_arm64.whl", hash = "sha256:c607bb3b57dc779d55e1554846352b4e358c10fff3abf3514a7a6601beebdb30"},
|
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|
{file = "psutil-5.9.5.tar.gz", hash = "sha256:5410638e4df39c54d957fc51ce03048acd8e6d60abc0f5107af51e5fb566eb3c"},
|
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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]
|
|
|
|
test = ["enum34", "ipaddress", "mock", "pywin32", "wmi"]
|
|
|
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|
|
|
|
[[package]]
|
|
|
|
name = "pyarrow"
|
2023-08-29 06:28:22 -06:00
|
|
|
version = "13.0.0"
|
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
|
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 = [
|
2023-08-29 06:28:22 -06:00
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{file = "pyarrow-13.0.0-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:e3ad79455c197a36eefbd90ad4aa832bece7f830a64396c15c61a0985e337287"},
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{file = "pyarrow-13.0.0-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:68fcd2dc1b7d9310b29a15949cdd0cb9bc34b6de767aff979ebf546020bf0ba0"},
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{file = "pyarrow-13.0.0-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:dc6fd330fd574c51d10638e63c0d00ab456498fc804c9d01f2a61b9264f2c5b2"},
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{file = "pyarrow-13.0.0-cp38-cp38-manylinux_2_28_aarch64.whl", hash = "sha256:e66442e084979a97bb66939e18f7b8709e4ac5f887e636aba29486ffbf373763"},
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|
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{file = "pyarrow-13.0.0-cp38-cp38-manylinux_2_28_x86_64.whl", hash = "sha256:0f6eff839a9e40e9c5610d3ff8c5bdd2f10303408312caf4c8003285d0b49565"},
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{file = "pyarrow-13.0.0-cp38-cp38-win_amd64.whl", hash = "sha256:8b30a27f1cddf5c6efcb67e598d7823a1e253d743d92ac32ec1eb4b6a1417867"},
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|
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{file = "pyarrow-13.0.0-cp39-cp39-macosx_10_14_x86_64.whl", hash = "sha256:09552dad5cf3de2dc0aba1c7c4b470754c69bd821f5faafc3d774bedc3b04bb7"},
|
|
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{file = "pyarrow-13.0.0-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:3896ae6c205d73ad192d2fc1489cd0edfab9f12867c85b4c277af4d37383c18c"},
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|
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{file = "pyarrow-13.0.0-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:6647444b21cb5e68b593b970b2a9a07748dd74ea457c7dadaa15fd469c48ada1"},
|
|
|
|
{file = "pyarrow-13.0.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:47663efc9c395e31d09c6aacfa860f4473815ad6804311c5433f7085415d62a7"},
|
|
|
|
{file = "pyarrow-13.0.0-cp39-cp39-manylinux_2_28_aarch64.whl", hash = "sha256:b9ba6b6d34bd2563345488cf444510588ea42ad5613df3b3509f48eb80250afd"},
|
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|
{file = "pyarrow-13.0.0-cp39-cp39-manylinux_2_28_x86_64.whl", hash = "sha256:d00d374a5625beeb448a7fa23060df79adb596074beb3ddc1838adb647b6ef09"},
|
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|
{file = "pyarrow-13.0.0-cp39-cp39-win_amd64.whl", hash = "sha256:c51afd87c35c8331b56f796eff954b9c7f8d4b7fef5903daf4e05fcf017d23a8"},
|
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|
|
{file = "pyarrow-13.0.0.tar.gz", hash = "sha256:83333726e83ed44b0ac94d8d7a21bbdee4a05029c3b1e8db58a863eec8fd8a33"},
|
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
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[package.dependencies]
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numpy = ">=1.16.6"
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[[package]]
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name = "pytest"
|
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version = "7.4.0"
|
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description = "pytest: simple powerful testing with Python"
|
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optional = false
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|
python-versions = ">=3.7"
|
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|
files = [
|
2023-07-04 12:23:55 -06:00
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|
|
{file = "pytest-7.4.0-py3-none-any.whl", hash = "sha256:78bf16451a2eb8c7a2ea98e32dc119fd2aa758f1d5d66dbf0a59d69a3969df32"},
|
|
|
|
{file = "pytest-7.4.0.tar.gz", hash = "sha256:b4bf8c45bd59934ed84001ad51e11b4ee40d40a1229d2c79f9c592b0a3f6bd8a"},
|
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\""}
|
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exceptiongroup = {version = ">=1.0.0rc8", markers = "python_version < \"3.11\""}
|
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|
iniconfig = "*"
|
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|
packaging = "*"
|
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pluggy = ">=0.12,<2.0"
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tomli = {version = ">=1.0.0", markers = "python_version < \"3.11\""}
|
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[package.extras]
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testing = ["argcomplete", "attrs (>=19.2.0)", "hypothesis (>=3.56)", "mock", "nose", "pygments (>=2.7.2)", "requests", "setuptools", "xmlschema"]
|
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[[package]]
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name = "python-dateutil"
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version = "2.8.2"
|
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description = "Extensions to the standard Python datetime module"
|
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optional = true
|
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|
python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,>=2.7"
|
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|
|
files = [
|
2023-07-27 06:50:45 -06:00
|
|
|
{file = "python-dateutil-2.8.2.tar.gz", hash = "sha256:0123cacc1627ae19ddf3c27a5de5bd67ee4586fbdd6440d9748f8abb483d3e86"},
|
|
|
|
{file = "python_dateutil-2.8.2-py2.py3-none-any.whl", hash = "sha256:961d03dc3453ebbc59dbdea9e4e11c5651520a876d0f4db161e8674aae935da9"},
|
|
|
|
]
|
feat(server): Add native support for PEFT Lora models (#762)
- Will detect `peft` model by finding `adapter_config.json`.
- This triggers a totally dedicated `download-weights` path
- This path, loads the adapter config, finds the base model_id
- It loads the base_model
- Then peft_model
- Then `merge_and_unload()`
- Then `save_pretrained(.., safe_serialization=True)
- Add back the config + tokenizer.merge_and_unload()`
- Then `save_pretrained(.., safe_serialization=True)
- Add back the config + tokenizer.
- The chosen location is a **local folder with the name of the user
chosen model id**
PROs:
- Easier than to expect user to merge manually
- Barely any change outside of `download-weights` command.
- This means everything will work in a single load.
- Should enable out of the box SM + HFE
CONs:
- Creates a local merged model in unusual location, potentially
not saved across docker reloads, or ovewriting some files if the PEFT
itself was local and containing other files in addition to the lora
Alternatives considered:
- Add `local_files_only=True` every where (discard because of massive
code change for not a good enough reason)
- Return something to `launcher` about the new model-id (a cleaner
location for this new model), but it would
introduce new communication somewhere where we didn't need it before.
- Using the HF cache folder and *stopping* the flow after
`download-weights` and asking user to restart with the actual local
model location
Fix #482
# What does this PR do?
<!--
Congratulations! You've made it this far! You're not quite done yet
though.
Once merged, your PR is going to appear in the release notes with the
title you set, so make sure it's a great title that fully reflects the
extent of your awesome contribution.
Then, please replace this with a description of the change and which
issue is fixed (if applicable). Please also include relevant motivation
and context. List any dependencies (if any) that are required for this
change.
Once you're done, someone will review your PR shortly (see the section
"Who can review?" below to tag some potential reviewers). They may
suggest changes to make the code even better. If no one reviewed your PR
after a week has passed, don't hesitate to post a new comment
@-mentioning the same persons---sometimes notifications get lost.
-->
<!-- Remove if not applicable -->
Fixes # (issue)
## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the
other checks if that's the case).
- [ ] Did you read the [contributor
guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests),
Pull Request section?
- [ ] Was this discussed/approved via a Github issue or the
[forum](https://discuss.huggingface.co/)? Please add a link
to it if that's the case.
- [ ] Did you make sure to update the documentation with your changes?
Here are the
[documentation
guidelines](https://github.com/huggingface/transformers/tree/main/docs),
and
[here are tips on formatting
docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation).
- [ ] Did you write any new necessary tests?
## Who can review?
Anyone in the community is free to review the PR once the tests have
passed. Feel free to tag
members/contributors who may be interested in your PR.
<!-- Your PR will be replied to 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"
|
|
|
|
version = "2023.3"
|
|
|
|
description = "World timezone definitions, modern and historical"
|
|
|
|
optional = true
|
|
|
|
python-versions = "*"
|
|
|
|
files = [
|
2023-07-27 06:50:45 -06:00
|
|
|
{file = "pytz-2023.3-py2.py3-none-any.whl", hash = "sha256:a151b3abb88eda1d4e34a9814df37de2a80e301e68ba0fd856fb9b46bfbbbffb"},
|
|
|
|
{file = "pytz-2023.3.tar.gz", hash = "sha256:1d8ce29db189191fb55338ee6d0387d82ab59f3d00eac103412d64e0ebd0c588"},
|
|
|
|
]
|
feat(server): Add native support for PEFT Lora models (#762)
- Will detect `peft` model by finding `adapter_config.json`.
- This triggers a totally dedicated `download-weights` path
- This path, loads the adapter config, finds the base model_id
- It loads the base_model
- Then peft_model
- Then `merge_and_unload()`
- Then `save_pretrained(.., safe_serialization=True)
- Add back the config + tokenizer.merge_and_unload()`
- Then `save_pretrained(.., safe_serialization=True)
- Add back the config + tokenizer.
- The chosen location is a **local folder with the name of the user
chosen model id**
PROs:
- Easier than to expect user to merge manually
- Barely any change outside of `download-weights` command.
- This means everything will work in a single load.
- Should enable out of the box SM + HFE
CONs:
- Creates a local merged model in unusual location, potentially
not saved across docker reloads, or ovewriting some files if the PEFT
itself was local and containing other files in addition to the lora
Alternatives considered:
- Add `local_files_only=True` every where (discard because of massive
code change for not a good enough reason)
- Return something to `launcher` about the new model-id (a cleaner
location for this new model), but it would
introduce new communication somewhere where we didn't need it before.
- Using the HF cache folder and *stopping* the flow after
`download-weights` and asking user to restart with the actual local
model location
Fix #482
# What does this PR do?
<!--
Congratulations! You've made it this far! You're not quite done yet
though.
Once merged, your PR is going to appear in the release notes with the
title you set, so make sure it's a great title that fully reflects the
extent of your awesome contribution.
Then, please replace this with a description of the change and which
issue is fixed (if applicable). Please also include relevant motivation
and context. List any dependencies (if any) that are required for this
change.
Once you're done, someone will review your PR shortly (see the section
"Who can review?" below to tag some potential reviewers). They may
suggest changes to make the code even better. If no one reviewed your PR
after a week has passed, don't hesitate to post a new comment
@-mentioning the same persons---sometimes notifications get lost.
-->
<!-- Remove if not applicable -->
Fixes # (issue)
## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the
other checks if that's the case).
- [ ] Did you read the [contributor
guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests),
Pull Request section?
- [ ] Was this discussed/approved via a Github issue or the
[forum](https://discuss.huggingface.co/)? Please add a link
to it if that's the case.
- [ ] Did you make sure to update the documentation with your changes?
Here are the
[documentation
guidelines](https://github.com/huggingface/transformers/tree/main/docs),
and
[here are tips on formatting
docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation).
- [ ] Did you write any new necessary tests?
## Who can review?
Anyone in the community is free to review the PR once the tests have
passed. Feel free to tag
members/contributors who may be interested in your PR.
<!-- Your PR will be replied to 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]]
|
2023-08-03 13:54:39 -06:00
|
|
|
name = "pyyaml"
|
|
|
|
version = "6.0.1"
|
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
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|
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]]
|
|
|
|
name = "regex"
|
2023-08-17 06:38:49 -06:00
|
|
|
version = "2023.8.8"
|
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 = "Alternative regular expression module, to replace re."
|
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optional = false
|
|
|
|
python-versions = ">=3.6"
|
|
|
|
files = [
|
2023-08-17 06:38:49 -06:00
|
|
|
{file = "regex-2023.8.8-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:88900f521c645f784260a8d346e12a1590f79e96403971241e64c3a265c8ecdb"},
|
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{file = "regex-2023.8.8.tar.gz", hash = "sha256:fcbdc5f2b0f1cd0f6a56cdb46fe41d2cce1e644e3b68832f3eeebc5fb0f7712e"},
|
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
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]
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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
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[[package]]
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name = "requests"
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version = "2.31.0"
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description = "Python HTTP for Humans."
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optional = false
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python-versions = ">=3.7"
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files = [
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2023-05-23 10:03:22 -06:00
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{file = "requests-2.31.0-py3-none-any.whl", hash = "sha256:58cd2187c01e70e6e26505bca751777aa9f2ee0b7f4300988b709f44e013003f"},
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{file = "requests-2.31.0.tar.gz", hash = "sha256:942c5a758f98d790eaed1a29cb6eefc7ffb0d1cf7af05c3d2791656dbd6ad1e1"},
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2023-02-13 05:02:45 -07:00
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]
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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
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[package.dependencies]
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certifi = ">=2017.4.17"
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charset-normalizer = ">=2,<4"
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idna = ">=2.5,<4"
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urllib3 = ">=1.21.1,<3"
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[package.extras]
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socks = ["PySocks (>=1.5.6,!=1.5.7)"]
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use-chardet-on-py3 = ["chardet (>=3.0.2,<6)"]
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[[package]]
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name = "safetensors"
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2023-08-29 06:28:22 -06:00
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version = "0.3.3"
|
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
|
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description = "Fast and Safe Tensor serialization"
|
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optional = false
|
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|
python-versions = "*"
|
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files = [
|
2023-08-29 06:28:22 -06:00
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{file = "safetensors-0.3.3-cp310-cp310-macosx_10_11_x86_64.whl", hash = "sha256:92e4d0c8b2836120fddd134474c5bda8963f322333941f8b9f643e5b24f041eb"},
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{file = "safetensors-0.3.3-cp310-cp310-macosx_11_0_x86_64.whl", hash = "sha256:3dcadb6153c42addc9c625a622ebde9293fabe1973f9ef31ba10fb42c16e8536"},
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|
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]
|
2023-08-11 08:46:08 -06:00
|
|
|
all = ["black (==22.3)", "click (==8.0.4)", "flake8 (>=3.8.3)", "flax (>=0.6.3)", "h5py (>=3.7.0)", "huggingface-hub (>=0.12.1)", "isort (>=5.5.4)", "jax (>=0.3.25)", "jaxlib (>=0.3.25)", "numpy (>=1.21.6)", "paddlepaddle (>=2.4.1)", "pytest (>=7.2.0)", "pytest-benchmark (>=4.0.0)", "setuptools-rust (>=1.5.2)", "tensorflow (==2.11.0)", "torch (>=1.10)"]
|
|
|
|
dev = ["black (==22.3)", "click (==8.0.4)", "flake8 (>=3.8.3)", "flax (>=0.6.3)", "h5py (>=3.7.0)", "huggingface-hub (>=0.12.1)", "isort (>=5.5.4)", "jax (>=0.3.25)", "jaxlib (>=0.3.25)", "numpy (>=1.21.6)", "paddlepaddle (>=2.4.1)", "pytest (>=7.2.0)", "pytest-benchmark (>=4.0.0)", "setuptools-rust (>=1.5.2)", "tensorflow (==2.11.0)", "torch (>=1.10)"]
|
2023-08-29 06:28:22 -06:00
|
|
|
jax = ["flax (>=0.6.3)", "jax (>=0.3.25)", "jaxlib (>=0.3.25)", "numpy (>=1.21.6)"]
|
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
|
|
|
numpy = ["numpy (>=1.21.6)"]
|
2023-08-29 06:28:22 -06:00
|
|
|
paddlepaddle = ["numpy (>=1.21.6)", "paddlepaddle (>=2.4.1)"]
|
2023-08-11 08:46:08 -06:00
|
|
|
pinned-tf = ["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)"]
|
2023-08-29 06:28:22 -06:00
|
|
|
tensorflow = ["numpy (>=1.21.6)", "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
|
|
|
testing = ["h5py (>=3.7.0)", "huggingface-hub (>=0.12.1)", "numpy (>=1.21.6)", "pytest (>=7.2.0)", "pytest-benchmark (>=4.0.0)", "setuptools-rust (>=1.5.2)"]
|
2023-08-29 06:28:22 -06:00
|
|
|
torch = ["numpy (>=1.21.6)", "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
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2023-08-03 15:00:59 -06:00
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[[package]]
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name = "scipy"
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2023-08-29 06:28:22 -06:00
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version = "1.11.2"
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2023-08-03 15:00:59 -06:00
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description = "Fundamental algorithms for scientific computing in Python"
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optional = false
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python-versions = "<3.13,>=3.9"
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files = [
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2023-08-29 06:28:22 -06:00
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2023-08-03 15:00:59 -06:00
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]
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[package.dependencies]
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numpy = ">=1.21.6,<1.28.0"
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[package.extras]
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dev = ["click", "cython-lint (>=0.12.2)", "doit (>=0.36.0)", "mypy", "pycodestyle", "pydevtool", "rich-click", "ruff", "types-psutil", "typing_extensions"]
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doc = ["jupytext", "matplotlib (>2)", "myst-nb", "numpydoc", "pooch", "pydata-sphinx-theme (==0.9.0)", "sphinx (!=4.1.0)", "sphinx-design (>=0.2.0)"]
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test = ["asv", "gmpy2", "mpmath", "pooch", "pytest", "pytest-cov", "pytest-timeout", "pytest-xdist", "scikit-umfpack", "threadpoolctl"]
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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?
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<!-- Remove if not applicable -->
Fixes # (issue)
## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the
other checks if that's the case).
- [ ] Did you read the [contributor
guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests),
Pull Request section?
- [ ] Was this discussed/approved via a Github issue or the
[forum](https://discuss.huggingface.co/)? Please add a link
to it if that's the case.
- [ ] Did you make sure to update the documentation with your changes?
Here are the
[documentation
guidelines](https://github.com/huggingface/transformers/tree/main/docs),
and
[here are tips on formatting
docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation).
- [ ] Did you write any new necessary tests?
## Who can review?
Anyone in the community is free to review the PR once the tests have
passed. Feel free to tag
members/contributors who may be interested in your PR.
<!-- Your PR will be replied to 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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[[package]]
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name = "sentencepiece"
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version = "0.1.99"
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description = "SentencePiece python wrapper"
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optional = false
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python-versions = "*"
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files = [
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2023-05-23 10:03:22 -06:00
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{file = "sentencepiece-0.1.99-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:6c030b081dc1e1bcc9fadc314b19b740715d3d566ad73a482da20d7d46fd444c"},
|
|
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{file = "sentencepiece-0.1.99-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:84dbe53e02e4f8a2e45d2ac3e430d5c83182142658e25edd76539b7648928727"},
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{file = "sentencepiece-0.1.99-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:0b0f55d0a0ee1719b4b04221fe0c9f0c3461dc3dabd77a035fa2f4788eb3ef9a"},
|
|
|
|
{file = "sentencepiece-0.1.99-cp39-cp39-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:18e800f206cd235dc27dc749299e05853a4e4332e8d3dfd81bf13d0e5b9007d9"},
|
|
|
|
{file = "sentencepiece-0.1.99-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:2ae1c40cda8f9d5b0423cfa98542735c0235e7597d79caf318855cdf971b2280"},
|
|
|
|
{file = "sentencepiece-0.1.99-cp39-cp39-win32.whl", hash = "sha256:c84ce33af12ca222d14a1cdd37bd76a69401e32bc68fe61c67ef6b59402f4ab8"},
|
|
|
|
{file = "sentencepiece-0.1.99-cp39-cp39-win_amd64.whl", hash = "sha256:350e5c74d739973f1c9643edb80f7cc904dc948578bcb1d43c6f2b173e5d18dd"},
|
|
|
|
{file = "sentencepiece-0.1.99.tar.gz", hash = "sha256:189c48f5cb2949288f97ccdb97f0473098d9c3dcf5a3d99d4eabe719ec27297f"},
|
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"
|
2023-08-29 06:28:22 -06:00
|
|
|
version = "68.1.2"
|
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
|
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 = [
|
2023-08-29 06:28:22 -06:00
|
|
|
{file = "setuptools-68.1.2-py3-none-any.whl", hash = "sha256:3d8083eed2d13afc9426f227b24fd1659489ec107c0e86cec2ffdde5c92e790b"},
|
|
|
|
{file = "setuptools-68.1.2.tar.gz", hash = "sha256:3d4dfa6d95f1b101d695a6160a7626e15583af71a5f52176efa5d39a054d475d"},
|
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]
|
2023-08-29 06:28:22 -06:00
|
|
|
docs = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "pygments-github-lexers (==0.0.5)", "rst.linker (>=1.9)", "sphinx (>=3.5,<=7.1.2)", "sphinx-favicon", "sphinx-hoverxref (<2)", "sphinx-inline-tabs", "sphinx-lint", "sphinx-notfound-page (==0.8.3)", "sphinx-reredirects", "sphinxcontrib-towncrier"]
|
|
|
|
testing = ["build[virtualenv]", "filelock (>=3.4.0)", "flake8-2020", "ini2toml[lite] (>=0.9)", "jaraco.develop (>=7.21)", "jaraco.envs (>=2.2)", "jaraco.path (>=3.2.0)", "pip (>=19.1)", "pytest (>=6)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-mypy (>=0.9.1)", "pytest-perf", "pytest-ruff", "pytest-timeout", "pytest-xdist", "tomli-w (>=1.0.0)", "virtualenv (>=13.0.0)", "wheel"]
|
feat(server): Add native support for PEFT Lora models (#762)
- Will detect `peft` model by finding `adapter_config.json`.
- This triggers a totally dedicated `download-weights` path
- This path, loads the adapter config, finds the base model_id
- It loads the base_model
- Then peft_model
- Then `merge_and_unload()`
- Then `save_pretrained(.., safe_serialization=True)
- Add back the config + tokenizer.merge_and_unload()`
- Then `save_pretrained(.., safe_serialization=True)
- Add back the config + tokenizer.
- The chosen location is a **local folder with the name of the user
chosen model id**
PROs:
- Easier than to expect user to merge manually
- Barely any change outside of `download-weights` command.
- This means everything will work in a single load.
- Should enable out of the box SM + HFE
CONs:
- Creates a local merged model in unusual location, potentially
not saved across docker reloads, or ovewriting some files if the PEFT
itself was local and containing other files in addition to the lora
Alternatives considered:
- Add `local_files_only=True` every where (discard because of massive
code change for not a good enough reason)
- Return something to `launcher` about the new model-id (a cleaner
location for this new model), but it would
introduce new communication somewhere where we didn't need it before.
- Using the HF cache folder and *stopping* the flow after
`download-weights` and asking user to restart with the actual local
model location
Fix #482
# What does this PR do?
<!--
Congratulations! You've made it this far! You're not quite done yet
though.
Once merged, your PR is going to appear in the release notes with the
title you set, so make sure it's a great title that fully reflects the
extent of your awesome contribution.
Then, please replace this with a description of the change and which
issue is fixed (if applicable). Please also include relevant motivation
and context. List any dependencies (if any) that are required for this
change.
Once you're done, someone will review your PR shortly (see the section
"Who can review?" below to tag some potential reviewers). They may
suggest changes to make the code even better. If no one reviewed your PR
after a week has passed, don't hesitate to post a new comment
@-mentioning the same persons---sometimes notifications get lost.
-->
<!-- Remove if not applicable -->
Fixes # (issue)
## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the
other checks if that's the case).
- [ ] Did you read the [contributor
guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests),
Pull Request section?
- [ ] Was this discussed/approved via a Github issue or the
[forum](https://discuss.huggingface.co/)? Please add a link
to it if that's the case.
- [ ] Did you make sure to update the documentation with your changes?
Here are the
[documentation
guidelines](https://github.com/huggingface/transformers/tree/main/docs),
and
[here are tips on formatting
docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation).
- [ ] Did you write any new necessary tests?
## Who can review?
Anyone in the community is free to review the PR once the tests have
passed. Feel free to tag
members/contributors who may be interested in your PR.
<!-- Your PR will be replied to more quickly if you can figure out the
right person to tag with @
@OlivierDehaene OR @Narsil
-->
2023-08-03 09:22:45 -06:00
|
|
|
testing-integration = ["build[virtualenv]", "filelock (>=3.4.0)", "jaraco.envs (>=2.2)", "jaraco.path (>=3.2.0)", "pytest", "pytest-enabler", "pytest-xdist", "tomli", "virtualenv (>=13.0.0)", "wheel"]
|
|
|
|
|
|
|
|
[[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 = [
|
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"
|
|
|
|
version = "1.12"
|
|
|
|
description = "Computer algebra system (CAS) in Python"
|
|
|
|
optional = false
|
|
|
|
python-versions = ">=3.8"
|
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|
|
files = [
|
2023-05-23 10:03:22 -06:00
|
|
|
{file = "sympy-1.12-py3-none-any.whl", hash = "sha256:c3588cd4295d0c0f603d0f2ae780587e64e2efeedb3521e46b9bb1d08d184fa5"},
|
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|
|
{file = "sympy-1.12.tar.gz", hash = "sha256:ebf595c8dac3e0fdc4152c51878b498396ec7f30e7a914d6071e674d49420fb8"},
|
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
|
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[package.dependencies]
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|
mpmath = ">=0.19"
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|
[[package]]
|
|
|
|
name = "texttable"
|
|
|
|
version = "1.6.7"
|
|
|
|
description = "module to create simple ASCII tables"
|
|
|
|
optional = true
|
|
|
|
python-versions = "*"
|
|
|
|
files = [
|
2023-07-27 04:28:10 -06:00
|
|
|
{file = "texttable-1.6.7-py2.py3-none-any.whl", hash = "sha256:b7b68139aa8a6339d2c320ca8b1dc42d13a7831a346b446cb9eb385f0c76310c"},
|
|
|
|
{file = "texttable-1.6.7.tar.gz", hash = "sha256:290348fb67f7746931bcdfd55ac7584ecd4e5b0846ab164333f0794b121760f2"},
|
|
|
|
]
|
feat(server): Add native support for PEFT Lora models (#762)
- Will detect `peft` model by finding `adapter_config.json`.
- This triggers a totally dedicated `download-weights` path
- This path, loads the adapter config, finds the base model_id
- It loads the base_model
- Then peft_model
- Then `merge_and_unload()`
- Then `save_pretrained(.., safe_serialization=True)
- Add back the config + tokenizer.merge_and_unload()`
- Then `save_pretrained(.., safe_serialization=True)
- Add back the config + tokenizer.
- The chosen location is a **local folder with the name of the user
chosen model id**
PROs:
- Easier than to expect user to merge manually
- Barely any change outside of `download-weights` command.
- This means everything will work in a single load.
- Should enable out of the box SM + HFE
CONs:
- Creates a local merged model in unusual location, potentially
not saved across docker reloads, or ovewriting some files if the PEFT
itself was local and containing other files in addition to the lora
Alternatives considered:
- Add `local_files_only=True` every where (discard because of massive
code change for not a good enough reason)
- Return something to `launcher` about the new model-id (a cleaner
location for this new model), but it would
introduce new communication somewhere where we didn't need it before.
- Using the HF cache folder and *stopping* the flow after
`download-weights` and asking user to restart with the actual local
model location
Fix #482
# What does this PR do?
<!--
Congratulations! You've made it this far! You're not quite done yet
though.
Once merged, your PR is going to appear in the release notes with the
title you set, so make sure it's a great title that fully reflects the
extent of your awesome contribution.
Then, please replace this with a description of the change and which
issue is fixed (if applicable). Please also include relevant motivation
and context. List any dependencies (if any) that are required for this
change.
Once you're done, someone will review your PR shortly (see the section
"Who can review?" below to tag some potential reviewers). They may
suggest changes to make the code even better. If no one reviewed your PR
after a week has passed, don't hesitate to post a new comment
@-mentioning the same persons---sometimes notifications get lost.
-->
<!-- Remove if not applicable -->
Fixes # (issue)
## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the
other checks if that's the case).
- [ ] Did you read the [contributor
guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests),
Pull Request section?
- [ ] Was this discussed/approved via a Github issue or the
[forum](https://discuss.huggingface.co/)? Please add a link
to it if that's the case.
- [ ] Did you make sure to update the documentation with your changes?
Here are the
[documentation
guidelines](https://github.com/huggingface/transformers/tree/main/docs),
and
[here are tips on formatting
docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation).
- [ ] Did you write any new necessary tests?
## Who can review?
Anyone in the community is free to review the PR once the tests have
passed. Feel free to tag
members/contributors who may be interested in your PR.
<!-- Your PR will be replied to 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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|
|
[[package]]
|
|
|
|
name = "tokenizers"
|
|
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|
version = "0.13.3"
|
|
|
|
description = "Fast and Customizable Tokenizers"
|
|
|
|
optional = false
|
|
|
|
python-versions = "*"
|
|
|
|
files = [
|
2023-04-11 08:38:22 -06:00
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|
|
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{file = "tokenizers-0.13.3-cp310-cp310-macosx_12_0_arm64.whl", hash = "sha256:4ef4c3e821730f2692489e926b184321e887f34fb8a6b80b8096b966ba663d07"},
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{file = "tokenizers-0.13.3-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:c5fd1a6a25353e9aa762e2aae5a1e63883cad9f4e997c447ec39d071020459bc"},
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{file = "tokenizers-0.13.3-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:ee0b1b311d65beab83d7a41c56a1e46ab732a9eed4460648e8eb0bd69fc2d059"},
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{file = "tokenizers-0.13.3-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:5ef4215284df1277dadbcc5e17d4882bda19f770d02348e73523f7e7d8b8d396"},
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{file = "tokenizers-0.13.3-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:a4d53976079cff8a033f778fb9adca2d9d69d009c02fa2d71a878b5f3963ed30"},
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{file = "tokenizers-0.13.3-cp310-cp310-win32.whl", hash = "sha256:1f0e3b4c2ea2cd13238ce43548959c118069db7579e5d40ec270ad77da5833ce"},
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{file = "tokenizers-0.13.3-cp310-cp310-win_amd64.whl", hash = "sha256:89649c00d0d7211e8186f7a75dfa1db6996f65edce4b84821817eadcc2d3c79e"},
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{file = "tokenizers-0.13.3-cp311-cp311-macosx_10_11_universal2.whl", hash = "sha256:56b726e0d2bbc9243872b0144515ba684af5b8d8cd112fb83ee1365e26ec74c8"},
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{file = "tokenizers-0.13.3-cp311-cp311-win32.whl", hash = "sha256:cc78d77f597d1c458bf0ea7c2a64b6aa06941c7a99cb135b5969b0278824d808"},
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{file = "tokenizers-0.13.3-cp311-cp311-win_amd64.whl", hash = "sha256:ecf182bf59bd541a8876deccf0360f5ae60496fd50b58510048020751cf1724c"},
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{file = "tokenizers-0.13.3-cp37-cp37m-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:4560dbdeaae5b7ee0d4e493027e3de6d53c991b5002d7ff95083c99e11dd5ac0"},
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{file = "tokenizers-0.13.3-cp37-cp37m-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:64064bd0322405c9374305ab9b4c07152a1474370327499911937fd4a76d004b"},
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{file = "tokenizers-0.13.3-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:b8c6e2ab0f2e3d939ca66aa1d596602105fe33b505cd2854a4c1717f704c51de"},
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{file = "tokenizers-0.13.3-cp37-cp37m-win32.whl", hash = "sha256:6cc29d410768f960db8677221e497226e545eaaea01aa3613fa0fdf2cc96cff4"},
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{file = "tokenizers-0.13.3-cp37-cp37m-win_amd64.whl", hash = "sha256:fc2a7fdf864554a0dacf09d32e17c0caa9afe72baf9dd7ddedc61973bae352d8"},
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{file = "tokenizers-0.13.3-cp38-cp38-macosx_10_11_x86_64.whl", hash = "sha256:8791dedba834c1fc55e5f1521be325ea3dafb381964be20684b92fdac95d79b7"},
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{file = "tokenizers-0.13.3-cp38-cp38-macosx_12_0_arm64.whl", hash = "sha256:d607a6a13718aeb20507bdf2b96162ead5145bbbfa26788d6b833f98b31b26e1"},
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{file = "tokenizers-0.13.3-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:3791338f809cd1bf8e4fee6b540b36822434d0c6c6bc47162448deee3f77d425"},
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{file = "tokenizers-0.13.3-cp38-cp38-win_amd64.whl", hash = "sha256:8e7b0cdeace87fa9e760e6a605e0ae8fc14b7d72e9fc19c578116f7287bb873d"},
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{file = "tokenizers-0.13.3-cp39-cp39-macosx_12_0_arm64.whl", hash = "sha256:a23ff602d0797cea1d0506ce69b27523b07e70f6dda982ab8cf82402de839088"},
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{file = "tokenizers-0.13.3-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:70ce07445050b537d2696022dafb115307abdffd2a5c106f029490f84501ef97"},
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{file = "tokenizers-0.13.3-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:280ffe95f50eaaf655b3a1dc7ff1d9cf4777029dbbc3e63a74e65a056594abc3"},
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{file = "tokenizers-0.13.3-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:97acfcec592f7e9de8cadcdcda50a7134423ac8455c0166b28c9ff04d227b371"},
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{file = "tokenizers-0.13.3-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:dd7730c98a3010cd4f523465867ff95cd9d6430db46676ce79358f65ae39797b"},
|
|
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{file = "tokenizers-0.13.3-cp39-cp39-win32.whl", hash = "sha256:48625a108029cb1ddf42e17a81b5a3230ba6888a70c9dc14e81bc319e812652d"},
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{file = "tokenizers-0.13.3-cp39-cp39-win_amd64.whl", hash = "sha256:bc0a6f1ba036e482db6453571c9e3e60ecd5489980ffd95d11dc9f960483d783"},
|
|
|
|
{file = "tokenizers-0.13.3.tar.gz", hash = "sha256:2e546dbb68b623008a5442353137fbb0123d311a6d7ba52f2667c8862a75af2e"},
|
|
|
|
]
|
feat(server): Add native support for PEFT Lora models (#762)
- Will detect `peft` model by finding `adapter_config.json`.
- This triggers a totally dedicated `download-weights` path
- This path, loads the adapter config, finds the base model_id
- It loads the base_model
- Then peft_model
- Then `merge_and_unload()`
- Then `save_pretrained(.., safe_serialization=True)
- Add back the config + tokenizer.merge_and_unload()`
- Then `save_pretrained(.., safe_serialization=True)
- Add back the config + tokenizer.
- The chosen location is a **local folder with the name of the user
chosen model id**
PROs:
- Easier than to expect user to merge manually
- Barely any change outside of `download-weights` command.
- This means everything will work in a single load.
- Should enable out of the box SM + HFE
CONs:
- Creates a local merged model in unusual location, potentially
not saved across docker reloads, or ovewriting some files if the PEFT
itself was local and containing other files in addition to the lora
Alternatives considered:
- Add `local_files_only=True` every where (discard because of massive
code change for not a good enough reason)
- Return something to `launcher` about the new model-id (a cleaner
location for this new model), but it would
introduce new communication somewhere where we didn't need it before.
- Using the HF cache folder and *stopping* the flow after
`download-weights` and asking user to restart with the actual local
model location
Fix #482
# What does this PR do?
<!--
Congratulations! You've made it this far! You're not quite done yet
though.
Once merged, your PR is going to appear in the release notes with the
title you set, so make sure it's a great title that fully reflects the
extent of your awesome contribution.
Then, please replace this with a description of the change and which
issue is fixed (if applicable). Please also include relevant motivation
and context. List any dependencies (if any) that are required for this
change.
Once you're done, someone will review your PR shortly (see the section
"Who can review?" below to tag some potential reviewers). They may
suggest changes to make the code even better. If no one reviewed your PR
after a week has passed, don't hesitate to post a new comment
@-mentioning the same persons---sometimes notifications get lost.
-->
<!-- Remove if not applicable -->
Fixes # (issue)
## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the
other checks if that's the case).
- [ ] Did you read the [contributor
guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests),
Pull Request section?
- [ ] Was this discussed/approved via a Github issue or the
[forum](https://discuss.huggingface.co/)? Please add a link
to it if that's the case.
- [ ] Did you make sure to update the documentation with your changes?
Here are the
[documentation
guidelines](https://github.com/huggingface/transformers/tree/main/docs),
and
[here are tips on formatting
docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation).
- [ ] Did you write any new necessary tests?
## Who can review?
Anyone in the community is free to review the PR once the tests have
passed. Feel free to tag
members/contributors who may be interested in your PR.
<!-- Your PR will be replied to 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 (==22.3)", "datasets", "numpy", "pytest", "requests"]
|
|
|
|
docs = ["setuptools-rust", "sphinx", "sphinx-rtd-theme"]
|
|
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|
testing = ["black (==22.3)", "datasets", "numpy", "pytest", "requests"]
|
|
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|
|
|
|
|
[[package]]
|
|
|
|
name = "tomli"
|
|
|
|
version = "2.0.1"
|
|
|
|
description = "A lil' TOML parser"
|
|
|
|
optional = false
|
|
|
|
python-versions = ">=3.7"
|
|
|
|
files = [
|
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"
|
2023-08-17 06:38:49 -06:00
|
|
|
version = "2.0.1"
|
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"
|
|
|
|
optional = false
|
|
|
|
python-versions = ">=3.8.0"
|
|
|
|
files = [
|
2023-08-17 06:38:49 -06:00
|
|
|
{file = "torch-2.0.1-cp310-cp310-manylinux1_x86_64.whl", hash = "sha256:8ced00b3ba471856b993822508f77c98f48a458623596a4c43136158781e306a"},
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{file = "torch-2.0.1-cp310-cp310-manylinux2014_aarch64.whl", hash = "sha256:359bfaad94d1cda02ab775dc1cc386d585712329bb47b8741607ef6ef4950747"},
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{file = "torch-2.0.1-cp310-none-macosx_10_9_x86_64.whl", hash = "sha256:567f84d657edc5582d716900543e6e62353dbe275e61cdc36eda4929e46df9e7"},
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{file = "torch-2.0.1-cp311-cp311-manylinux1_x86_64.whl", hash = "sha256:e617b1d0abaf6ced02dbb9486803abfef0d581609b09641b34fa315c9c40766d"},
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{file = "torch-2.0.1-cp311-none-macosx_10_9_x86_64.whl", hash = "sha256:ef654427d91600129864644e35deea761fb1fe131710180b952a6f2e2207075e"},
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{file = "torch-2.0.1-cp311-none-macosx_11_0_arm64.whl", hash = "sha256:25aa43ca80dcdf32f13da04c503ec7afdf8e77e3a0183dd85cd3e53b2842e527"},
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{file = "torch-2.0.1-cp38-cp38-manylinux1_x86_64.whl", hash = "sha256:5ef3ea3d25441d3957348f7e99c7824d33798258a2bf5f0f0277cbcadad2e20d"},
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{file = "torch-2.0.1-cp38-cp38-manylinux2014_aarch64.whl", hash = "sha256:0882243755ff28895e8e6dc6bc26ebcf5aa0911ed81b2a12f241fc4b09075b13"},
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{file = "torch-2.0.1-cp38-cp38-win_amd64.whl", hash = "sha256:f66aa6b9580a22b04d0af54fcd042f52406a8479e2b6a550e3d9f95963e168c8"},
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{file = "torch-2.0.1-cp38-none-macosx_10_9_x86_64.whl", hash = "sha256:1adb60d369f2650cac8e9a95b1d5758e25d526a34808f7448d0bd599e4ae9072"},
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{file = "torch-2.0.1-cp38-none-macosx_11_0_arm64.whl", hash = "sha256:1bcffc16b89e296826b33b98db5166f990e3b72654a2b90673e817b16c50e32b"},
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{file = "torch-2.0.1-cp39-cp39-manylinux1_x86_64.whl", hash = "sha256:e10e1597f2175365285db1b24019eb6f04d53dcd626c735fc502f1e8b6be9875"},
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{file = "torch-2.0.1-cp39-cp39-manylinux2014_aarch64.whl", hash = "sha256:423e0ae257b756bb45a4b49072046772d1ad0c592265c5080070e0767da4e490"},
|
|
|
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{file = "torch-2.0.1-cp39-cp39-win_amd64.whl", hash = "sha256:8742bdc62946c93f75ff92da00e3803216c6cce9b132fbca69664ca38cfb3e18"},
|
|
|
|
{file = "torch-2.0.1-cp39-none-macosx_10_9_x86_64.whl", hash = "sha256:c62df99352bd6ee5a5a8d1832452110435d178b5164de450831a3a8cc14dc680"},
|
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{file = "torch-2.0.1-cp39-none-macosx_11_0_arm64.whl", hash = "sha256:671a2565e3f63b8fe8e42ae3e36ad249fe5e567435ea27b94edaa672a7d0c416"},
|
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 = "*"
|
|
|
|
jinja2 = "*"
|
|
|
|
networkx = "*"
|
|
|
|
sympy = "*"
|
|
|
|
typing-extensions = "*"
|
|
|
|
|
|
|
|
[package.extras]
|
|
|
|
opt-einsum = ["opt-einsum (>=3.3)"]
|
|
|
|
|
|
|
|
[[package]]
|
|
|
|
name = "tqdm"
|
2023-08-17 06:38:49 -06:00
|
|
|
version = "4.66.1"
|
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 = "Fast, Extensible Progress Meter"
|
|
|
|
optional = false
|
|
|
|
python-versions = ">=3.7"
|
|
|
|
files = [
|
2023-08-17 06:38:49 -06:00
|
|
|
{file = "tqdm-4.66.1-py3-none-any.whl", hash = "sha256:d302b3c5b53d47bce91fea46679d9c3c6508cf6332229aa1e7d8653723793386"},
|
|
|
|
{file = "tqdm-4.66.1.tar.gz", hash = "sha256:d88e651f9db8d8551a62556d3cff9e3034274ca5d66e93197cf2490e2dcb69c7"},
|
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]
|
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]]
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|
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name = "transformers"
|
2023-08-29 06:28:22 -06:00
|
|
|
version = "4.32.1"
|
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 = "State-of-the-art Machine Learning for JAX, PyTorch and TensorFlow"
|
|
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optional = false
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2023-08-11 08:46:08 -06:00
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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
|
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files = [
|
2023-08-29 06:28:22 -06:00
|
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|
{file = "transformers-4.32.1-py3-none-any.whl", hash = "sha256:b930d3dbd907a3f300cf49e54d63a56f8a0ab16b01a2c2a61ecff37c6de1da08"},
|
|
|
|
{file = "transformers-4.32.1.tar.gz", hash = "sha256:1edc8ae1de357d97c3d36b04412aa63d55e6fc0c4b39b419a7d380ed947d2252"},
|
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
|
|
|
|
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|
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[package.dependencies]
|
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filelock = "*"
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2023-08-29 06:28:22 -06:00
|
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|
huggingface-hub = ">=0.15.1,<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
|
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numpy = ">=1.17"
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packaging = ">=20.0"
|
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pyyaml = ">=5.1"
|
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regex = "!=2019.12.17"
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|
|
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requests = "*"
|
2023-08-11 08:46:08 -06:00
|
|
|
safetensors = ">=0.3.1"
|
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
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tokenizers = ">=0.11.1,<0.11.3 || >0.11.3,<0.14"
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tqdm = ">=4.27"
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[package.extras]
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2023-08-11 08:46:08 -06:00
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accelerate = ["accelerate (>=0.20.3)"]
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agents = ["Pillow (<10.0.0)", "accelerate (>=0.20.3)", "datasets (!=2.5.0)", "diffusers", "opencv-python", "sentencepiece (>=0.1.91,!=0.1.92)", "torch (>=1.9,!=1.12.0)"]
|
2023-08-29 06:28:22 -06:00
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all = ["Pillow (<10.0.0)", "accelerate (>=0.20.3)", "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)", "librosa", "onnxconverter-common", "optax (>=0.0.8,<=0.1.4)", "optuna", "phonemizer", "protobuf", "pyctcdecode (>=0.4.0)", "ray[tune]", "sentencepiece (>=0.1.91,!=0.1.92)", "sigopt", "tensorflow (>=2.6,<2.14)", "tensorflow-text (<2.14)", "tf2onnx", "timm", "tokenizers (>=0.11.1,!=0.11.3,<0.14)", "torch (>=1.9,!=1.12.0)", "torchaudio", "torchvision"]
|
2023-08-11 08:46:08 -06:00
|
|
|
audio = ["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
|
|
|
codecarbon = ["codecarbon (==1.2.0)"]
|
2023-08-11 08:46:08 -06:00
|
|
|
deepspeed = ["accelerate (>=0.20.3)", "deepspeed (>=0.9.3)"]
|
|
|
|
deepspeed-testing = ["GitPython (<3.1.19)", "accelerate (>=0.20.3)", "beautifulsoup4", "black (>=23.1,<24.0)", "cookiecutter (==1.7.3)", "datasets (!=2.5.0)", "deepspeed (>=0.9.3)", "dill (<0.3.5)", "evaluate (>=0.2.0)", "faiss-cpu", "hf-doc-builder (>=0.3.0)", "nltk", "optuna", "parameterized", "protobuf", "psutil", "pytest (>=7.2.0)", "pytest-timeout", "pytest-xdist", "rjieba", "rouge-score (!=0.0.7,!=0.0.8,!=0.1,!=0.1.1)", "sacrebleu (>=1.4.12,<2.0.0)", "sacremoses", "sentencepiece (>=0.1.91,!=0.1.92)", "timeout-decorator"]
|
2023-08-29 06:28:22 -06:00
|
|
|
dev = ["GitPython (<3.1.19)", "Pillow (<10.0.0)", "accelerate (>=0.20.3)", "av (==9.2.0)", "beautifulsoup4", "black (>=23.1,<24.0)", "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)", "hf-doc-builder", "hf-doc-builder (>=0.3.0)", "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)", "librosa", "nltk", "onnxconverter-common", "optax (>=0.0.8,<=0.1.4)", "optuna", "parameterized", "phonemizer", "protobuf", "psutil", "pyctcdecode (>=0.4.0)", "pytest (>=7.2.0)", "pytest-timeout", "pytest-xdist", "ray[tune]", "rhoknp (>=1.1.0,<1.3.1)", "rjieba", "rouge-score (!=0.0.7,!=0.0.8,!=0.1,!=0.1.1)", "ruff (>=0.0.241,<=0.0.259)", "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)", "tensorflow (>=2.6,<2.14)", "tensorflow-text (<2.14)", "tf2onnx", "timeout-decorator", "timm", "tokenizers (>=0.11.1,!=0.11.3,<0.14)", "torch (>=1.9,!=1.12.0)", "torchaudio", "torchvision", "unidic (>=1.0.2)", "unidic-lite (>=1.0.7)", "urllib3 (<2.0.0)"]
|
2023-08-11 08:46:08 -06:00
|
|
|
dev-tensorflow = ["GitPython (<3.1.19)", "Pillow (<10.0.0)", "beautifulsoup4", "black (>=23.1,<24.0)", "cookiecutter (==1.7.3)", "datasets (!=2.5.0)", "dill (<0.3.5)", "evaluate (>=0.2.0)", "faiss-cpu", "hf-doc-builder", "hf-doc-builder (>=0.3.0)", "isort (>=5.5.4)", "kenlm", "keras-nlp (>=0.3.1)", "librosa", "nltk", "onnxconverter-common", "onnxruntime (>=1.4.0)", "onnxruntime-tools (>=1.4.2)", "parameterized", "phonemizer", "protobuf", "psutil", "pyctcdecode (>=0.4.0)", "pytest (>=7.2.0)", "pytest-timeout", "pytest-xdist", "rjieba", "rouge-score (!=0.0.7,!=0.0.8,!=0.1,!=0.1.1)", "ruff (>=0.0.241,<=0.0.259)", "sacrebleu (>=1.4.12,<2.0.0)", "sacremoses", "scikit-learn", "sentencepiece (>=0.1.91,!=0.1.92)", "tensorflow (>=2.6,<2.14)", "tensorflow-text (<2.14)", "tf2onnx", "timeout-decorator", "tokenizers (>=0.11.1,!=0.11.3,<0.14)", "urllib3 (<2.0.0)"]
|
|
|
|
dev-torch = ["GitPython (<3.1.19)", "Pillow (<10.0.0)", "accelerate (>=0.20.3)", "beautifulsoup4", "black (>=23.1,<24.0)", "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)", "hf-doc-builder", "hf-doc-builder (>=0.3.0)", "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)", "pytest (>=7.2.0)", "pytest-timeout", "pytest-xdist", "ray[tune]", "rhoknp (>=1.1.0,<1.3.1)", "rjieba", "rouge-score (!=0.0.7,!=0.0.8,!=0.1,!=0.1.1)", "ruff (>=0.0.241,<=0.0.259)", "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)", "timeout-decorator", "timm", "tokenizers (>=0.11.1,!=0.11.3,<0.14)", "torch (>=1.9,!=1.12.0)", "torchaudio", "torchvision", "unidic (>=1.0.2)", "unidic-lite (>=1.0.7)", "urllib3 (<2.0.0)"]
|
2023-08-29 06:28:22 -06:00
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docs = ["Pillow (<10.0.0)", "accelerate (>=0.20.3)", "av (==9.2.0)", "codecarbon (==1.2.0)", "decord (==0.6.0)", "flax (>=0.4.1,<=0.7.0)", "hf-doc-builder", "jax (>=0.4.1,<=0.4.13)", "jaxlib (>=0.4.1,<=0.4.13)", "kenlm", "keras-nlp (>=0.3.1)", "librosa", "onnxconverter-common", "optax (>=0.0.8,<=0.1.4)", "optuna", "phonemizer", "protobuf", "pyctcdecode (>=0.4.0)", "ray[tune]", "sentencepiece (>=0.1.91,!=0.1.92)", "sigopt", "tensorflow (>=2.6,<2.14)", "tensorflow-text (<2.14)", "tf2onnx", "timm", "tokenizers (>=0.11.1,!=0.11.3,<0.14)", "torch (>=1.9,!=1.12.0)", "torchaudio", "torchvision"]
|
feat(server): Add native support for PEFT Lora models (#762)
- Will detect `peft` model by finding `adapter_config.json`.
- This triggers a totally dedicated `download-weights` path
- This path, loads the adapter config, finds the base model_id
- It loads the base_model
- Then peft_model
- Then `merge_and_unload()`
- Then `save_pretrained(.., safe_serialization=True)
- Add back the config + tokenizer.merge_and_unload()`
- Then `save_pretrained(.., safe_serialization=True)
- Add back the config + tokenizer.
- The chosen location is a **local folder with the name of the user
chosen model id**
PROs:
- Easier than to expect user to merge manually
- Barely any change outside of `download-weights` command.
- This means everything will work in a single load.
- Should enable out of the box SM + HFE
CONs:
- Creates a local merged model in unusual location, potentially
not saved across docker reloads, or ovewriting some files if the PEFT
itself was local and containing other files in addition to the lora
Alternatives considered:
- Add `local_files_only=True` every where (discard because of massive
code change for not a good enough reason)
- Return something to `launcher` about the new model-id (a cleaner
location for this new model), but it would
introduce new communication somewhere where we didn't need it before.
- Using the HF cache folder and *stopping* the flow after
`download-weights` and asking user to restart with the actual local
model location
Fix #482
# What does this PR do?
<!--
Congratulations! You've made it this far! You're not quite done yet
though.
Once merged, your PR is going to appear in the release notes with the
title you set, so make sure it's a great title that fully reflects the
extent of your awesome contribution.
Then, please replace this with a description of the change and which
issue is fixed (if applicable). Please also include relevant motivation
and context. List any dependencies (if any) that are required for this
change.
Once you're done, someone will review your PR shortly (see the section
"Who can review?" below to tag some potential reviewers). They may
suggest changes to make the code even better. If no one reviewed your PR
after a week has passed, don't hesitate to post a new comment
@-mentioning the same persons---sometimes notifications get lost.
-->
<!-- Remove if not applicable -->
Fixes # (issue)
## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the
other checks if that's the case).
- [ ] Did you read the [contributor
guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests),
Pull Request section?
- [ ] Was this discussed/approved via a Github issue or the
[forum](https://discuss.huggingface.co/)? Please add a link
to it if that's the case.
- [ ] Did you make sure to update the documentation with your changes?
Here are the
[documentation
guidelines](https://github.com/huggingface/transformers/tree/main/docs),
and
[here are tips on formatting
docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation).
- [ ] Did you write any new necessary tests?
## Who can review?
Anyone in the community is free to review the PR once the tests have
passed. Feel free to tag
members/contributors who may be interested in your PR.
<!-- Your PR will be replied to 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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|
docs-specific = ["hf-doc-builder"]
|
|
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|
fairscale = ["fairscale (>0.3)"]
|
2023-08-29 06:28:22 -06:00
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|
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)"]
|
2023-08-11 08:46:08 -06:00
|
|
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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"]
|
|
|
|
integrations = ["optuna", "ray[tune]", "sigopt"]
|
2023-08-11 08:46:08 -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)"]
|
|
|
|
natten = ["natten (>=0.14.6)"]
|
|
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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"]
|
|
|
|
quality = ["GitPython (<3.1.19)", "black (>=23.1,<24.0)", "datasets (!=2.5.0)", "hf-doc-builder (>=0.3.0)", "isort (>=5.5.4)", "ruff (>=0.0.241,<=0.0.259)", "urllib3 (<2.0.0)"]
|
|
|
|
ray = ["ray[tune]"]
|
|
|
|
retrieval = ["datasets (!=2.5.0)", "faiss-cpu"]
|
|
|
|
sagemaker = ["sagemaker (>=2.31.0)"]
|
2023-08-11 08:46:08 -06:00
|
|
|
sentencepiece = ["protobuf", "sentencepiece (>=0.1.91,!=0.1.92)"]
|
|
|
|
serving = ["fastapi", "pydantic (<2)", "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"]
|
2023-08-11 08:46:08 -06:00
|
|
|
speech = ["kenlm", "librosa", "phonemizer", "pyctcdecode (>=0.4.0)", "torchaudio"]
|
|
|
|
testing = ["GitPython (<3.1.19)", "beautifulsoup4", "black (>=23.1,<24.0)", "cookiecutter (==1.7.3)", "datasets (!=2.5.0)", "dill (<0.3.5)", "evaluate (>=0.2.0)", "faiss-cpu", "hf-doc-builder (>=0.3.0)", "nltk", "parameterized", "protobuf", "psutil", "pytest (>=7.2.0)", "pytest-timeout", "pytest-xdist", "rjieba", "rouge-score (!=0.0.7,!=0.0.8,!=0.1,!=0.1.1)", "sacrebleu (>=1.4.12,<2.0.0)", "sacremoses", "timeout-decorator"]
|
|
|
|
tf = ["keras-nlp (>=0.3.1)", "onnxconverter-common", "tensorflow (>=2.6,<2.14)", "tensorflow-text (<2.14)", "tf2onnx"]
|
|
|
|
tf-cpu = ["keras-nlp (>=0.3.1)", "onnxconverter-common", "tensorflow-cpu (>=2.6,<2.14)", "tensorflow-text (<2.14)", "tf2onnx"]
|
|
|
|
tf-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
|
|
|
timm = ["timm"]
|
|
|
|
tokenizers = ["tokenizers (>=0.11.1,!=0.11.3,<0.14)"]
|
2023-08-11 08:46:08 -06:00
|
|
|
torch = ["accelerate (>=0.20.3)", "torch (>=1.9,!=1.12.0)"]
|
|
|
|
torch-speech = ["kenlm", "librosa", "phonemizer", "pyctcdecode (>=0.4.0)", "torchaudio"]
|
|
|
|
torch-vision = ["Pillow (<10.0.0)", "torchvision"]
|
2023-08-29 06:28:22 -06:00
|
|
|
torchhub = ["filelock", "huggingface-hub (>=0.15.1,<1.0)", "importlib-metadata", "numpy (>=1.17)", "packaging (>=20.0)", "protobuf", "regex (!=2019.12.17)", "requests", "sentencepiece (>=0.1.91,!=0.1.92)", "tokenizers (>=0.11.1,!=0.11.3,<0.14)", "torch (>=1.9,!=1.12.0)", "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)"]
|
2023-08-11 08:46:08 -06:00
|
|
|
vision = ["Pillow (<10.0.0)"]
|
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
|
|
|
|
|
|
|
[[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 = [
|
2022-10-08 04:30:12 -06:00
|
|
|
{file = "typer-0.6.1-py3-none-any.whl", hash = "sha256:54b19e5df18654070a82f8c2aa1da456a4ac16a2a83e6dcd9f170e291c56338e"},
|
|
|
|
{file = "typer-0.6.1.tar.gz", hash = "sha256:2d5720a5e63f73eaf31edaa15f6ab87f35f0690f8ca233017d7d23d743a91d73"},
|
|
|
|
]
|
feat(server): Add native support for PEFT Lora models (#762)
- Will detect `peft` model by finding `adapter_config.json`.
- This triggers a totally dedicated `download-weights` path
- This path, loads the adapter config, finds the base model_id
- It loads the base_model
- Then peft_model
- Then `merge_and_unload()`
- Then `save_pretrained(.., safe_serialization=True)
- Add back the config + tokenizer.merge_and_unload()`
- Then `save_pretrained(.., safe_serialization=True)
- Add back the config + tokenizer.
- The chosen location is a **local folder with the name of the user
chosen model id**
PROs:
- Easier than to expect user to merge manually
- Barely any change outside of `download-weights` command.
- This means everything will work in a single load.
- Should enable out of the box SM + HFE
CONs:
- Creates a local merged model in unusual location, potentially
not saved across docker reloads, or ovewriting some files if the PEFT
itself was local and containing other files in addition to the lora
Alternatives considered:
- Add `local_files_only=True` every where (discard because of massive
code change for not a good enough reason)
- Return something to `launcher` about the new model-id (a cleaner
location for this new model), but it would
introduce new communication somewhere where we didn't need it before.
- Using the HF cache folder and *stopping* the flow after
`download-weights` and asking user to restart with the actual local
model location
Fix #482
# What does this PR do?
<!--
Congratulations! You've made it this far! You're not quite done yet
though.
Once merged, your PR is going to appear in the release notes with the
title you set, so make sure it's a great title that fully reflects the
extent of your awesome contribution.
Then, please replace this with a description of the change and which
issue is fixed (if applicable). Please also include relevant motivation
and context. List any dependencies (if any) that are required for this
change.
Once you're done, someone will review your PR shortly (see the section
"Who can review?" below to tag some potential reviewers). They may
suggest changes to make the code even better. If no one reviewed your PR
after a week has passed, don't hesitate to post a new comment
@-mentioning the same persons---sometimes notifications get lost.
-->
<!-- Remove if not applicable -->
Fixes # (issue)
## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the
other checks if that's the case).
- [ ] Did you read the [contributor
guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests),
Pull Request section?
- [ ] Was this discussed/approved via a Github issue or the
[forum](https://discuss.huggingface.co/)? Please add a link
to it if that's the case.
- [ ] Did you make sure to update the documentation with your changes?
Here are the
[documentation
guidelines](https://github.com/huggingface/transformers/tree/main/docs),
and
[here are tips on formatting
docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation).
- [ ] Did you write any new necessary tests?
## Who can review?
Anyone in the community is free to review the PR once the tests have
passed. Feel free to tag
members/contributors who may be interested in your PR.
<!-- Your PR will be replied to 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]
|
|
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|
click = ">=7.1.1,<9.0.0"
|
|
|
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|
|
|
|
[package.extras]
|
|
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|
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)"]
|
|
|
|
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|
|
|
[[package]]
|
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name = "typing-extensions"
|
|
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|
version = "4.7.1"
|
|
|
|
description = "Backported and Experimental Type Hints for Python 3.7+"
|
|
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|
optional = false
|
|
|
|
python-versions = ">=3.7"
|
|
|
|
files = [
|
2023-07-04 12:23:55 -06:00
|
|
|
{file = "typing_extensions-4.7.1-py3-none-any.whl", hash = "sha256:440d5dd3af93b060174bf433bccd69b0babc3b15b1a8dca43789fd7f61514b36"},
|
|
|
|
{file = "typing_extensions-4.7.1.tar.gz", hash = "sha256:b75ddc264f0ba5615db7ba217daeb99701ad295353c45f9e95963337ceeeffb2"},
|
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"
|
|
|
|
version = "2023.3"
|
|
|
|
description = "Provider of IANA time zone data"
|
|
|
|
optional = true
|
|
|
|
python-versions = ">=2"
|
|
|
|
files = [
|
2023-07-27 06:50:45 -06:00
|
|
|
{file = "tzdata-2023.3-py2.py3-none-any.whl", hash = "sha256:7e65763eef3120314099b6939b5546db7adce1e7d6f2e179e3df563c70511eda"},
|
|
|
|
{file = "tzdata-2023.3.tar.gz", hash = "sha256:11ef1e08e54acb0d4f95bdb1be05da659673de4acbd21bf9c69e94cc5e907a3a"},
|
|
|
|
]
|
feat(server): Add native support for PEFT Lora models (#762)
- Will detect `peft` model by finding `adapter_config.json`.
- This triggers a totally dedicated `download-weights` path
- This path, loads the adapter config, finds the base model_id
- It loads the base_model
- Then peft_model
- Then `merge_and_unload()`
- Then `save_pretrained(.., safe_serialization=True)
- Add back the config + tokenizer.merge_and_unload()`
- Then `save_pretrained(.., safe_serialization=True)
- Add back the config + tokenizer.
- The chosen location is a **local folder with the name of the user
chosen model id**
PROs:
- Easier than to expect user to merge manually
- Barely any change outside of `download-weights` command.
- This means everything will work in a single load.
- Should enable out of the box SM + HFE
CONs:
- Creates a local merged model in unusual location, potentially
not saved across docker reloads, or ovewriting some files if the PEFT
itself was local and containing other files in addition to the lora
Alternatives considered:
- Add `local_files_only=True` every where (discard because of massive
code change for not a good enough reason)
- Return something to `launcher` about the new model-id (a cleaner
location for this new model), but it would
introduce new communication somewhere where we didn't need it before.
- Using the HF cache folder and *stopping* the flow after
`download-weights` and asking user to restart with the actual local
model location
Fix #482
# What does this PR do?
<!--
Congratulations! You've made it this far! You're not quite done yet
though.
Once merged, your PR is going to appear in the release notes with the
title you set, so make sure it's a great title that fully reflects the
extent of your awesome contribution.
Then, please replace this with a description of the change and which
issue is fixed (if applicable). Please also include relevant motivation
and context. List any dependencies (if any) that are required for this
change.
Once you're done, someone will review your PR shortly (see the section
"Who can review?" below to tag some potential reviewers). They may
suggest changes to make the code even better. If no one reviewed your PR
after a week has passed, don't hesitate to post a new comment
@-mentioning the same persons---sometimes notifications get lost.
-->
<!-- Remove if not applicable -->
Fixes # (issue)
## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the
other checks if that's the case).
- [ ] Did you read the [contributor
guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests),
Pull Request section?
- [ ] Was this discussed/approved via a Github issue or the
[forum](https://discuss.huggingface.co/)? Please add a link
to it if that's the case.
- [ ] Did you make sure to update the documentation with your changes?
Here are the
[documentation
guidelines](https://github.com/huggingface/transformers/tree/main/docs),
and
[here are tips on formatting
docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation).
- [ ] Did you write any new necessary tests?
## Who can review?
Anyone in the community is free to review the PR once the tests have
passed. Feel free to tag
members/contributors who may be interested in your PR.
<!-- Your PR will be replied to 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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|
[[package]]
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name = "urllib3"
|
2023-08-03 13:54:39 -06:00
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|
version = "2.0.4"
|
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
|
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description = "HTTP library with thread-safe connection pooling, file post, and more."
|
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|
optional = false
|
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|
python-versions = ">=3.7"
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files = [
|
2023-08-03 13:54:39 -06:00
|
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|
{file = "urllib3-2.0.4-py3-none-any.whl", hash = "sha256:de7df1803967d2c2a98e4b11bb7d6bd9210474c46e8a0401514e3a42a75ebde4"},
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{file = "urllib3-2.0.4.tar.gz", hash = "sha256:8d22f86aae8ef5e410d4f539fde9ce6b2113a001bb4d189e0aed70642d602b11"},
|
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
|
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[package.extras]
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brotli = ["brotli (>=1.0.9)", "brotlicffi (>=0.8.0)"]
|
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secure = ["certifi", "cryptography (>=1.9)", "idna (>=2.0.0)", "pyopenssl (>=17.1.0)", "urllib3-secure-extra"]
|
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socks = ["pysocks (>=1.5.6,!=1.5.7,<2.0)"]
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zstd = ["zstandard (>=0.18.0)"]
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[[package]]
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name = "win32-setctime"
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version = "1.1.0"
|
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|
|
description = "A small Python utility to set file creation time on Windows"
|
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optional = false
|
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|
python-versions = ">=3.5"
|
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|
|
files = [
|
2023-01-05 04:01:23 -07:00
|
|
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{file = "win32_setctime-1.1.0-py3-none-any.whl", hash = "sha256:231db239e959c2fe7eb1d7dc129f11172354f98361c4fa2d6d2d7e278baa8aad"},
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{file = "win32_setctime-1.1.0.tar.gz", hash = "sha256:15cf5750465118d6929ae4de4eb46e8edae9a5634350c01ba582df868e932cb2"},
|
|
|
|
]
|
feat(server): Add native support for PEFT Lora models (#762)
- Will detect `peft` model by finding `adapter_config.json`.
- This triggers a totally dedicated `download-weights` path
- This path, loads the adapter config, finds the base model_id
- It loads the base_model
- Then peft_model
- Then `merge_and_unload()`
- Then `save_pretrained(.., safe_serialization=True)
- Add back the config + tokenizer.merge_and_unload()`
- Then `save_pretrained(.., safe_serialization=True)
- Add back the config + tokenizer.
- The chosen location is a **local folder with the name of the user
chosen model id**
PROs:
- Easier than to expect user to merge manually
- Barely any change outside of `download-weights` command.
- This means everything will work in a single load.
- Should enable out of the box SM + HFE
CONs:
- Creates a local merged model in unusual location, potentially
not saved across docker reloads, or ovewriting some files if the PEFT
itself was local and containing other files in addition to the lora
Alternatives considered:
- Add `local_files_only=True` every where (discard because of massive
code change for not a good enough reason)
- Return something to `launcher` about the new model-id (a cleaner
location for this new model), but it would
introduce new communication somewhere where we didn't need it before.
- Using the HF cache folder and *stopping* the flow after
`download-weights` and asking user to restart with the actual local
model location
Fix #482
# What does this PR do?
<!--
Congratulations! You've made it this far! You're not quite done yet
though.
Once merged, your PR is going to appear in the release notes with the
title you set, so make sure it's a great title that fully reflects the
extent of your awesome contribution.
Then, please replace this with a description of the change and which
issue is fixed (if applicable). Please also include relevant motivation
and context. List any dependencies (if any) that are required for this
change.
Once you're done, someone will review your PR shortly (see the section
"Who can review?" below to tag some potential reviewers). They may
suggest changes to make the code even better. If no one reviewed your PR
after a week has passed, don't hesitate to post a new comment
@-mentioning the same persons---sometimes notifications get lost.
-->
<!-- Remove if not applicable -->
Fixes # (issue)
## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the
other checks if that's the case).
- [ ] Did you read the [contributor
guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests),
Pull Request section?
- [ ] Was this discussed/approved via a Github issue or the
[forum](https://discuss.huggingface.co/)? Please add a link
to it if that's the case.
- [ ] Did you make sure to update the documentation with your changes?
Here are the
[documentation
guidelines](https://github.com/huggingface/transformers/tree/main/docs),
and
[here are tips on formatting
docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation).
- [ ] Did you write any new necessary tests?
## Who can review?
Anyone in the community is free to review the PR once the tests have
passed. Feel free to tag
members/contributors who may be interested in your PR.
<!-- Your PR will be replied to 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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|
|
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|
|
[package.extras]
|
|
|
|
dev = ["black (>=19.3b0)", "pytest (>=4.6.2)"]
|
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[[package]]
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name = "wrapt"
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version = "1.15.0"
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description = "Module for decorators, wrappers and monkey patching."
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optional = false
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python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,>=2.7"
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files = [
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2023-03-03 03:26:27 -07:00
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|
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"
|
2023-08-03 13:54:39 -06:00
|
|
|
version = "3.3.0"
|
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
|
|
|
description = "Python binding for xxHash"
|
|
|
|
optional = true
|
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 = [
|
2023-08-03 13:54:39 -06:00
|
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2023-07-27 06:50:45 -06:00
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]
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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?
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Fixes # (issue)
## Before submitting
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docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation).
- [ ] Did you write any new necessary tests?
## Who can review?
Anyone in the community is free to review the PR once the tests have
passed. Feel free to tag
members/contributors who may be interested in your PR.
<!-- Your PR will be replied to more quickly if you can figure out the
right person to tag with @
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-->
2023-08-03 09:22:45 -06:00
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[[package]]
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name = "yarl"
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version = "1.9.2"
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description = "Yet another URL library"
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optional = true
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python-versions = ">=3.7"
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files = [
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2023-07-27 06:50:45 -06:00
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]
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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?
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Fixes # (issue)
## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the
other checks if that's the case).
- [ ] Did you read the [contributor
guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests),
Pull Request section?
- [ ] Was this discussed/approved via a Github issue or the
[forum](https://discuss.huggingface.co/)? Please add a link
to it if that's the case.
- [ ] Did you make sure to update the documentation with your changes?
Here are the
[documentation
guidelines](https://github.com/huggingface/transformers/tree/main/docs),
and
[here are tips on formatting
docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation).
- [ ] Did you write any new necessary tests?
## Who can review?
Anyone in the community is free to review the PR once the tests have
passed. Feel free to tag
members/contributors who may be interested in your PR.
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2023-08-03 09:22:45 -06:00
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[package.dependencies]
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idna = ">=2.0"
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multidict = ">=4.0"
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[extras]
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accelerate = ["accelerate"]
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bnb = ["bitsandbytes"]
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quantize = ["accelerate", "datasets", "texttable"]
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[metadata]
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lock-version = "2.0"
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2023-08-03 15:00:59 -06:00
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python-versions = ">=3.9,<3.13"
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2023-08-29 06:28:22 -06:00
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content-hash = "f2ef5f41a172d14985367a385ad6ce844c8c05b2d68d9ddcc11b41f581921c96"
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