Commit Graph

47 Commits

Author SHA1 Message Date
Nicolas Patry 8390e251d9
Making `make install` work better by default. (#2004)
# What does this PR do?

Making `make install` a much better sane default to start local dev
environments.

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2024-06-04 19:38:46 +02:00
Nicolas Patry d32e33bd48
Fix seeded output. (#1949)
# What does this PR do?

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2024-05-24 15:36:13 +02:00
drbh 40213c957f
Pali gemma modeling (#1895)
This PR adds paligemma modeling code

Blog post: https://huggingface.co/blog/paligemma
Transformers PR: https://github.com/huggingface/transformers/pull/30814

install the latest changes and run with
```bash
# get the weights
# text-generation-server download-weights gv-hf/PaliGemma-base-224px-hf

# run TGI
text-generation-launcher --model-id gv-hf/PaliGemma-base-224px-hf
```


basic example sending various requests
```python
from huggingface_hub import InferenceClient

client = InferenceClient("http://127.0.0.1:3000")


images = [
    "https://huggingface.co/datasets/hf-internal-testing/fixtures-captioning/resolve/main/cow_beach_1.png",
    "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/transformers/rabbit.png",
]

prompts = [
    "What animal is in this image?",
    "Name three colors in this image.",
    "What are 10 colors in this image?",
    "Where is the cow standing?",
    "answer en Where is the cow standing?",
    "Is there a bird in the image?",
    "Is ther a cow in the image?",
    "Is there a rabbit in the image?",
    "how many birds are in the image?",
    "how many rabbits are in the image?",
]

for img in images:
    print(f"\nImage: {img.split('/')[-1]}")
    for prompt in prompts:
        inputs = f"![]({img}){prompt}\n"
        json_data = {
            "inputs": inputs,
            "parameters": {
                "max_new_tokens": 30,
                "do_sample": False,
            },
        }
        generated_output = client.text_generation(prompt, max_new_tokens=30, stream=False)
        print([f"{prompt}\n{generated_output}"])

```

---------

Co-authored-by: Nicolas Patry <patry.nicolas@protonmail.com>
2024-05-16 06:58:47 +02:00
Nicolas Patry d348d2b28f
Granite support? (#1882)
# What does this PR do?

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2024-05-13 13:46:29 +02:00
Nicolas Patry dccab72549
(chore): torch 2.3.0 (#1833)
# What does this PR do?

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2024-04-30 18:15:35 +02:00
Nicolas Patry f9ee2c41b9
Upgrading all versions. (#1759) 2024-04-18 17:17:40 +02:00
abhishek thakur 10d9083b2d
Update libraries (#1713)
Co-authored-by: Nicolas Patry <patry.nicolas@protonmail.com>
2024-04-11 10:37:35 +02:00
OlivierDehaene 1e9bcd9dd8
feat: cohere (#1660) 2024-03-22 17:59:25 +01:00
OlivierDehaene 4139054b82
v1.4.1 (#1568) 2024-02-16 17:50:57 +01:00
Jason Stillerman 39af000cb9
Update to peft 0.8.2 (#1537)
# What does this PR do?

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2024-02-08 12:44:04 +01:00
OlivierDehaene c2d4a3b5c7
v1.4.0 (#1494) 2024-01-26 19:04:57 +01:00
OlivierDehaene 9b56d3fbf5
feat: relax mistral requirements (#1351)
Close #1253 
Close #1279
2023-12-15 12:52:24 +01:00
OlivierDehaene 35509ff5de
chore: update to torch 2.1.0 (#1182)
Close #1142
2023-11-23 13:38:50 +01:00
Nicolas Patry 00b8f36fba
Prepare for v1.1.1 (#1100)
# What does this PR do?

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2023-10-05 16:09:49 +02:00
Nicolas Patry c5de7cd886
Add AWQ quantization inference support (#1019) (#1054)
# Add AWQ quantization inference support

Fixes
https://github.com/huggingface/text-generation-inference/issues/781

This PR (partially) adds support for AWQ quantization for inference.
More information on AWQ [here](https://arxiv.org/abs/2306.00978). In
general, AWQ is faster and more accurate than GPTQ, which is currently
supported by TGI.

This PR installs 4-bit GEMM custom CUDA kernels released by AWQ authors
(in `requirements.txt`, just one line change).

Quick way to test this PR would be bring up TGI as follows:

```
text-generation-server download-weights abhinavkulkarni/codellama-CodeLlama-7b-Python-hf-w4-g128-awq

text-generation-launcher \
--huggingface-hub-cache ~/.cache/huggingface/hub/ \
--model-id abhinavkulkarni/codellama-CodeLlama-7b-Python-hf-w4-g128-awq \
--trust-remote-code --port 8080 \
--max-input-length 2048 --max-total-tokens 4096 --max-batch-prefill-tokens 4096 \
--quantize awq
```

Please note:
* This PR was tested with FlashAttention v2 and vLLM.
* This PR adds support for AWQ inference, not quantizing the models.
That needs to be done outside of TGI, instructions

[here](f084f40bd9).
* This PR only adds support for `FlashLlama` models for now.
* Multi-GPU setup has not been tested. 
* No integration tests have been added so far, will add later if
maintainers are interested in this change.
* This PR can be tested on any of the models released

[here](https://huggingface.co/abhinavkulkarni?sort_models=downloads#models).

Please refer to the linked issue for benchmarks for

[abhinavkulkarni/meta-llama-Llama-2-7b-chat-hf-w4-g128-awq](https://huggingface.co/abhinavkulkarni/meta-llama-Llama-2-7b-chat-hf-w4-g128-awq)
vs

[TheBloke/Llama-2-7b-Chat-GPTQ](https://huggingface.co/TheBloke/Llama-2-7b-Chat-GPTQ).

Please note, AWQ has released faster (and in case of Llama, fused)
kernels for 4-bit GEMM, currently at the top of the `main` branch at
https://github.com/mit-han-lab/llm-awq, but this PR uses an older commit
that has been tested to work. We can switch to latest commit later on.

## Who can review?

@OlivierDehaene OR @Narsil

---------



# What does this PR do?

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---------

Co-authored-by: Abhinav M Kulkarni <abhinavkulkarni@gmail.com>
Co-authored-by: Abhinav Kulkarni <abhinav@concentric.ai>
2023-09-25 15:31:27 +02:00
Nicolas Patry 5485c142e8
New release. (#941)
# What does this PR do?

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2023-08-29 14:28:22 +02:00
Nicolas Patry bce5e22444
Adding Idefics multi modal model. (#842)
Co-Authored-By: Victor Sanh <victorsanh@gmail.com>


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---------

Co-authored-by: Victor Sanh <victorsanh@gmail.com>
2023-08-17 14:38:49 +02:00
Nicolas Patry cc7bb5084d
Upgrade transformers (fix protobuf==3.20 issue) (#795)
# What does this PR do?

Fixes #531

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2023-08-11 16:46:08 +02:00
Nicolas Patry 16fadcec57
Merge BNB 4bit. (#770)
# What does this PR do?


See #626 
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Co-authored-by: krzim <zimmerk4@live.com>
2023-08-03 23:00:59 +02:00
Nicolas Patry 6ec5288ab7
This should prevent the PyTorch overriding. (#767)
# What does this PR do?

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2023-08-03 21:54:39 +02:00
Nicolas Patry ac736fd89c
feat(server): Add native support for PEFT Lora models (#762)
- Will detect `peft` model by finding `adapter_config.json`.
- This triggers a totally dedicated `download-weights` path
- This path, loads the adapter config, finds the base model_id
- It loads the base_model
- Then peft_model
- Then `merge_and_unload()`
- Then `save_pretrained(.., safe_serialization=True)
- Add back the config + tokenizer.merge_and_unload()`
- Then `save_pretrained(.., safe_serialization=True)
- Add back the config + tokenizer.
- The chosen location is a **local folder with the name of the user
  chosen model id**

PROs:

- Easier than to expect user to merge manually
- Barely any change outside of `download-weights` command.
- This means everything will work in a single load.
- Should enable out of the box SM + HFE

CONs:

- Creates a local merged model in unusual location, potentially
  not saved across docker reloads, or ovewriting some files if the PEFT
  itself was local and containing other files in addition to the lora

Alternatives considered:
- Add `local_files_only=True` every where (discard because of massive
  code change for not a good enough reason)
- Return something to `launcher` about the new model-id (a cleaner
  location for this new model), but it would
  introduce new communication somewhere where we didn't need it before.
- Using the HF cache folder and *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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      to it if that's the case.
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2023-08-03 17:22:45 +02:00
OlivierDehaene 2efd46ef95 fix(server): fix missing datasets in quantize 2023-07-27 14:50:45 +02:00
OlivierDehaene 8bd0adb135
fix(server): fix quantization python requirements (#708) 2023-07-27 12:28:10 +02:00
OlivierDehaene 31e2253ae7
feat(server): use latest flash attention commit (#543)
@njhill FYI
2023-07-04 20:23:55 +02:00
Nicolas Patry 1da07e85aa
feat(server): Add Non flash MPT. (#514)
# What does this PR do?


This adds a non flash version of MPT.
Flash is harder because we need to create a bias ready cuda kernel of
flash attention.

Fixes
https://github.com/huggingface/text-generation-inference/issues/361
Fixes
https://github.com/huggingface/text-generation-inference/issues/491
Fixes
https://github.com/huggingface/text-generation-inference/issues/290
2023-07-03 13:01:46 +02:00
Nicolas Patry aefde28b45
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?

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Fixes # (issue)


## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the
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      Pull Request section?
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[forum](https://discuss.huggingface.co/)? Please add a link
      to it if that's the case.
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Here are the
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---------

Co-authored-by: Ubuntu <ubuntu@ip-172-31-41-161.ec2.internal>
Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2023-06-26 12:27:01 +02:00
OlivierDehaene 94377efa78
chore(sever): update requirements (#357)
Fixes #338
2023-05-23 18:03:22 +02:00
OlivierDehaene 37b64a5c10
chore(server): update safetensors version (#235) 2023-04-25 13:50:56 +02:00
OlivierDehaene 98a3e0d135
chore(server): update huggingface-hub (#227) 2023-04-24 15:57:13 +02:00
OlivierDehaene 6837b2eb77
fix(docker): remove unused dependencies (#205) 2023-04-19 19:39:31 +02:00
OlivierDehaene 5d27f5259b
fix(server): fix hf_transfer issue with private repos (#203) 2023-04-19 17:36:16 +02:00
OlivierDehaene 7a1ba58557
fix(docker): fix docker image dependencies (#187) 2023-04-17 00:26:47 +02:00
OlivierDehaene 64347b05ff
fix(ci): fix CVE in github-slug-action (#174) 2023-04-13 12:43:05 +02:00
OlivierDehaene 299217c95c
feat(server): add flash attention llama (#144) 2023-04-11 16:38:22 +02:00
OlivierDehaene 2d39f199ae
feat(server): update to hf_transfer==0.1.2 (#93) 2023-03-03 11:26:27 +01:00
OlivierDehaene 17bc841b1b
feat(server): enable hf-transfer (#76) 2023-02-18 14:04:11 +01:00
OlivierDehaene 9af454142a
feat: add distributed tracing (#62) 2023-02-13 13:02:45 +01:00
OlivierDehaene 54fec93193
fix(server): fix seeding with multiple shards (#44) 2023-01-31 16:01:15 +01:00
OlivierDehaene fcc2c5fcbf
feat(launcher): Log server stdout (#19)
Co-authored-by: Nick Hill <nickhill@us.ibm.com>
2023-01-05 12:01:23 +01:00
OlivierDehaene a2985036aa
feat(server): Add model tests (#6) 2022-12-08 18:49:33 +01:00
OlivierDehaene 4236e41b0d feat(server): Improved doc 2022-11-07 12:53:56 +01:00
OlivierDehaene b3b7ea0d74 feat: Use json formatter by default in docker image 2022-11-02 17:29:56 +01:00
OlivierDehaene 09674e6df9 feat(server): Support bitsandbytes 2022-10-27 14:25:29 +02:00
Nicolas Patry c8ce9b2515
feat(server): Use safetensors
Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com>
2022-10-22 20:00:15 +02:00
Olivier Dehaene f16f2f5ae1 v0.1.0 2022-10-20 19:14:44 +02:00
Olivier Dehaene bf99afe916 feat: Docker image 2022-10-14 15:56:21 +02:00
Olivier Dehaene 295831a481 Init 2022-10-08 12:30:12 +02:00