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# What does this PR do?

Fixes #1056

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# 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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---------
Co-authored-by: Abhinav M Kulkarni <abhinavkulkarni@gmail.com>
Co-authored-by: Abhinav Kulkarni <abhinav@concentric.ai>

# What does this PR do?

Fixes #1038

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# What does this PR do?

Fixes #1004

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if there's no cuda. disable custom kernels

# What does this PR do?

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Signed-off-by: Wang, Yi A <yi.a.wang@intel.com>

Co-authored-by: Omar Sanseviero <osanseviero@gmail.com>
Co-authored-by: Mishig <mishig.davaadorj@coloradocollege.edu>
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
Co-authored-by: OlivierDehaene <olivier@huggingface.co>

Co-authored-by: Nicolas Patry <patry.nicolas@protonmail.com>
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

Co-authored-by: Nicolas Patry <patry.nicolas@protonmail.com>
Co-authored-by: Omar Sanseviero <osanseviero@gmail.com>
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

As more and more people begin to use Baichuan's open-source models, the
influence of Baichuan models is growing, especially in China. Many
community members are interested in adding support for Baichuan models
to TGI. Meanwhile, Baichuan is a very open company, and in the future,
it plans to open-source more and more models, taking all this into
consideration, we would like to add support for the Baichuan model to
TGI. To do this, we need to make some changes, which we hope can be
merged into the main branch of TGI. In the future, we would be happy to
help maintain support for Baichuan models in TGI. We sincerely hope that
our pull request can be accepted. Thank you.

By the way, the changes of this time mainly for supporting Baichuan-7B.

---------
Co-authored-by: xiaoyuze <xiaoyuze@baichuan.com>
Co-authored-by: Nicolas Patry <patry.nicolas@protonmail.com>

# What does this PR do?

Fix __call__ vs forward.

To reproduce error just launch:
TheBloke/WizardLM-Uncensored-Falcon-7B-GPTQ with gptq (it fails because
falcon code uses `__call__` instead for `forward` calls)

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IDK what else to add in this guide, I looked for relevant code in TGI
codebase and saw that it's used in quantization as well (maybe I could
add that?)

Proposal to fix
https://github.com/huggingface/text-generation-inference/issues/962

# What does this PR do?
The
[changes](https://github.com/huggingface/text-generation-inference/pull/986/files#diff-b72e45030214e50c8ff6e3be837057b3f3368b9779fd942ca680f949fe069eafR176)
disabling exllama on old compute had unintended consequences of not
setting `use_exllama` to `False` if `HAS_EXLLAMA` equals `False` **and**
`CAN_EXLLAMA` equals `False`. This fixes this.

## Before submitting
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@OlivierDehaene @Narsil 

Anyone in the community is free to review the PR once the tests have
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Co-authored-by: OlivierDehaene <olivier@huggingface.co>

PR for conceptual guide on flash attention. I will add more info unless
I'm told otherwise.

---------
Co-authored-by: Nicolas Patry <patry.nicolas@protonmail.com>
Co-authored-by: Omar Sanseviero <osanseviero@gmail.com>

# What does this PR do?

sync the version for text-generation.

# What does this PR do?

Disabling exllama on old compute.

Exllama + T4 don't play nice together, this will disable it right away
to avoid issues at runtime.

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Looks like an error

This should allow users to use either Pydantic 2 or Pydantic 1.

I couldn't run all tests locally because I reran them too often and got
rate limited, but I believe this is sufficient.

# What does this PR do?

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transposing the fixes from
https://github.com/huggingface/transformers/pull/25787

# What does this PR do?

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# What does this PR do?
During the safetensor conversion, duplicate weights are removed.
However, which of the duplicates gets removed, differs per checkpoint.
In some, like `h2oai/h2ogpt-oig-oasst1-falcon-40b`, the weight
`transformer.word_embeddings.weightSafetensor` gets removed. In others,
`lm_head.weight` gets removed. Long story long, we need to support both.

Originally, f0181436 mapped `lm_head` to `word_embeddings`. Then ac736fd8
switched this around. This commit merges them and allows for both.

## Before submitting
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## Who can review?

@Narsil, you wrote both commits I referenced in this PR. I think you'll
understand this change :)

# What does this PR do?

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---------
Co-authored-by: Vincent Brouwers <vincent.brouwers@ing.com>

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cc @osanseviero

---------
Co-authored-by: Omar Sanseviero <osanseviero@gmail.com>

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Co-authored-by: Lucain <lucainp@gmail.com>
Co-authored-by: Merve Noyan <merveenoyan@gmail.com>

Co-Authored-By: Victor Sanh <victorsanh@gmail.com>


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---------
Co-authored-by: Victor Sanh <victorsanh@gmail.com>

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# What does this PR do?

- New "falcon" layout on this repo
- No alibi
- `transformers` already modifying cache layout in our stead (same
  modifications).
- Output is garbage. Not sure why.

Does not fix #826 but it's a step.

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List of changes

- No need to specify `model` in `text_generation` if it's already
specified in `InferenceClient`
- I separated the explanation of `stream=True` and `details=True`
- I found the details explanation a bit repetitive (it says two times
what it returns), so removed a sentence
- Add mention of async client

# What does this PR do?

Fixes #843 
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Co-authored-by: Nicolas Patry <patry.nicolas@protonmail.com>