2022-10-08 04:30:12 -06:00
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[tool.poetry]
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2023-03-07 10:52:22 -07:00
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name = "text-generation-server"
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2024-03-29 12:17:24 -06:00
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version = "1.4.5"
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2023-02-03 04:43:37 -07:00
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description = "Text Generation Inference Python gRPC Server"
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2022-10-08 04:30:12 -06:00
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authors = ["Olivier Dehaene <olivier@huggingface.co>"]
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2022-10-17 06:59:00 -06:00
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[tool.poetry.scripts]
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2023-03-07 10:52:22 -07:00
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text-generation-server = 'text_generation_server.cli:app'
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2022-10-17 06:59:00 -06:00
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2022-10-08 04:30:12 -06:00
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[tool.poetry.dependencies]
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2023-08-03 15:00:59 -06:00
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python = ">=3.9,<3.13"
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2022-10-08 04:30:12 -06:00
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protobuf = "^4.21.7"
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2023-01-05 04:01:23 -07:00
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grpcio = "^1.51.1"
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grpcio-status = "^1.51.1"
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grpcio-reflection = "^1.51.1"
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grpc-interceptor = "^0.15.0"
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2022-10-08 04:30:12 -06:00
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typer = "^0.6.1"
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2024-03-15 06:23:26 -06:00
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accelerate = { version = "^0.28.0", optional = true }
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bitsandbytes = { version = "^0.43.0", optional = true }
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2024-03-22 10:59:25 -06:00
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safetensors = "^0.4"
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2023-01-05 04:01:23 -07:00
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loguru = "^0.6.0"
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2023-02-13 05:02:45 -07:00
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opentelemetry-api = "^1.15.0"
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opentelemetry-exporter-otlp = "^1.15.0"
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opentelemetry-instrumentation-grpc = "^0.36b0"
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2023-03-03 03:26:27 -07:00
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hf-transfer = "^0.1.2"
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2023-04-11 08:38:22 -06:00
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sentencepiece = "^0.1.97"
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2023-12-15 04:52:24 -07:00
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tokenizers = "^0.15.0"
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huggingface-hub = "^0.19.3"
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2024-03-22 10:59:25 -06:00
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transformers = "^4.38"
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2023-07-03 05:01:46 -06:00
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einops = "^0.6.1"
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2023-07-27 06:50:45 -06:00
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texttable = { version = "^1.6.7", optional = true }
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datasets = { version = "^2.14.0", optional = true }
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2024-03-22 10:59:25 -06:00
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peft = { version = "^0.9", optional = true }
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2023-11-23 05:38:50 -07:00
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torch = { version = "^2.1.1", optional = true }
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2023-08-03 15:00:59 -06:00
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scipy = "^1.11.1"
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2023-08-17 06:38:49 -06:00
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pillow = "^10.0.0"
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2024-03-21 10:45:56 -06:00
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outlines= { version = "^0.0.36", optional = true }
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2022-10-08 04:30:12 -06:00
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2022-10-28 11:24:00 -06:00
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[tool.poetry.extras]
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2023-11-23 05:38:50 -07:00
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torch = ["torch"]
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2023-04-19 11:39:31 -06:00
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accelerate = ["accelerate"]
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2022-10-28 11:24:00 -06:00
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bnb = ["bitsandbytes"]
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2023-11-23 05:38:50 -07:00
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peft = ["peft"]
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2023-07-27 06:50:45 -06:00
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quantize = ["texttable", "datasets", "accelerate"]
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2024-02-16 09:50:57 -07:00
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outlines = ["outlines"]
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2022-10-28 11:24:00 -06:00
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2022-10-08 04:30:12 -06:00
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[tool.poetry.group.dev.dependencies]
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2023-02-13 05:02:45 -07:00
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grpcio-tools = "^1.51.1"
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2023-04-13 04:43:05 -06:00
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pytest = "^7.3.0"
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2022-10-08 04:30:12 -06:00
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2023-08-03 13:54:39 -06:00
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[[tool.poetry.source]]
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name = "pytorch-gpu-src"
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2023-11-23 05:38:50 -07:00
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url = "https://download.pytorch.org/whl/cu121"
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2023-08-03 13:54:39 -06:00
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priority = "explicit"
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2023-05-22 07:05:32 -06:00
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[tool.pytest.ini_options]
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markers = ["private: marks tests as requiring an admin hf token (deselect with '-m \"not private\"')"]
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2022-10-08 04:30:12 -06:00
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[build-system]
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Add AWQ quantization inference support (#1019) (#1054)
# Add AWQ quantization inference support
Fixes
https://github.com/huggingface/text-generation-inference/issues/781
This PR (partially) adds support for AWQ quantization for inference.
More information on AWQ [here](https://arxiv.org/abs/2306.00978). In
general, AWQ is faster and more accurate than GPTQ, which is currently
supported by TGI.
This PR installs 4-bit GEMM custom CUDA kernels released by AWQ authors
(in `requirements.txt`, just one line change).
Quick way to test this PR would be bring up TGI as follows:
```
text-generation-server download-weights abhinavkulkarni/codellama-CodeLlama-7b-Python-hf-w4-g128-awq
text-generation-launcher \
--huggingface-hub-cache ~/.cache/huggingface/hub/ \
--model-id abhinavkulkarni/codellama-CodeLlama-7b-Python-hf-w4-g128-awq \
--trust-remote-code --port 8080 \
--max-input-length 2048 --max-total-tokens 4096 --max-batch-prefill-tokens 4096 \
--quantize awq
```
Please note:
* This PR was tested with FlashAttention v2 and vLLM.
* This PR adds support for AWQ inference, not quantizing the models.
That needs to be done outside of TGI, instructions
[here](https://github.com/mit-han-lab/llm-awq/tree/f084f40bd996f3cf3a0633c1ad7d9d476c318aaa).
* This PR only adds support for `FlashLlama` models for now.
* Multi-GPU setup has not been tested.
* No integration tests have been added so far, will add later if
maintainers are interested in this change.
* This PR can be tested on any of the models released
[here](https://huggingface.co/abhinavkulkarni?sort_models=downloads#models).
Please refer to the linked issue for benchmarks for
[abhinavkulkarni/meta-llama-Llama-2-7b-chat-hf-w4-g128-awq](https://huggingface.co/abhinavkulkarni/meta-llama-Llama-2-7b-chat-hf-w4-g128-awq)
vs
[TheBloke/Llama-2-7b-Chat-GPTQ](https://huggingface.co/TheBloke/Llama-2-7b-Chat-GPTQ).
Please note, AWQ has released faster (and in case of Llama, fused)
kernels for 4-bit GEMM, currently at the top of the `main` branch at
https://github.com/mit-han-lab/llm-awq, but this PR uses an older commit
that has been tested to work. We can switch to latest commit later on.
## Who can review?
@OlivierDehaene OR @Narsil
---------
# What does this PR do?
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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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---------
Co-authored-by: Abhinav M Kulkarni <abhinavkulkarni@gmail.com>
Co-authored-by: Abhinav Kulkarni <abhinav@concentric.ai>
2023-09-25 07:31:27 -06:00
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requires = [
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"poetry-core>=1.0.0",
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]
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2022-10-08 04:30:12 -06:00
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build-backend = "poetry.core.masonry.api"
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