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# What does this PR do?


This should enable more aggressive by default stacking, meaning better
throughput (in throughput constrained environements).

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This PR allows the `CompletionRequest.prompt` to be sent as a string or
array of strings. When an array is sent the first value will be used if
it's a string; otherwise the according error will be thrown

Fixes:
https://github.com/huggingface/text-generation-inference/issues/1690
Similar to: https://github.com/vllm-project/vllm/pull/323/files

# What does this PR do?

- Renamed `max_input_length` into `max_input_tokens` for consistency
(backward compatible change, will yell if both are set.)
- Will now use the config for `max_input_tokens` `max_total_token` and
`max_batch_total_tokens`.
- Capping the values to 16k in order to save VRAM on behalf of users
(overriddable by simply setting the values).

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# What does this PR do?

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---------
Co-authored-by: Dong Shin <d0104.shin@gmail.com>

This reverts commit b83aab9b.

# What does this PR do?

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# What does this PR do?

```
text-generation-launcher --model-id XXX # Uses cuda graphs by default
text-generation-launcher --model-id XXX --cuda-graphs "1,2"  #Restrict the number of cuda graphs which saves VRAM
text-generation-launcher --model-id XXX --cuda-graphs "0"  # Disabling it entirely
```
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This WIP PR starts to add grammar support via outlines, currently this
PR supports very simple regex grammars and does not optimize for
precompiling or caching grammar fsm's.

todo:
- [X] add simple outlines guidance to `NextTokenChooser`
- [X] update protos for grammar
- [X] update generation params API
- [X] constrain simple grammar
- [ ] support parsing more complex grammar into fsm
- [ ] support all outline support grammar types
- [ ] explore optimizations to avoid recompiling grammars

guided request
```bash
curl -s 'http://localhost:3000/generate' \
--header 'Content-Type: application/json' \
--data-raw '{
    "inputs": "make an email for david: \n",
    "parameters": {
        "max_new_tokens": 6,
        "grammar": "[\\w-]+@([\\w-]+\\.)+[\\w-]+"
    }
}' | jq
```
response
```json
{
  "generated_text": "david@example.com"
}
```

unguided request
```bash
curl -s 'http://localhost:3000/generate' \
--header 'Content-Type: application/json' \
--data '{
    "inputs": "make an email for david: \n",
    "parameters": {
        "max_new_tokens": 6
    }
}' | jq
```
response
```json
{
  "generated_text": "    email = 'david"
}
```

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

Some hardware require a maximum batch size.

# What does this PR do?

Attempts to fix a link from Using TGI CLI to Installation.


## Before submitting
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other checks if that's the case).
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      Pull Request section?
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This PR adds the `tokenizer-config-path` to the launcher and passes it
to the router

Fixes:
https://github.com/huggingface/text-generation-inference/pull/1427

# What does this PR do?

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---------
Co-authored-by: Andres Restrepo <andres@thelinuxkid.com>

Fixes a link in doc

# What does this PR do?

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### Broken highlighting (current)

<img width="800" alt="Screenshot 2023-09-28 at 22 38 15"
src="https://github.com/huggingface/text-generation-inference/assets/11827707/1f07c356-2c3c-4ff0-8ca5-54a032b05d48">

### Fixed highlighting (this PR)

<img width="800" alt="image"
src="https://github.com/huggingface/text-generation-inference/assets/11827707/87fe750d-c26e-4801-95cc-86859a2df52d">

Wrap code blocks in `launcher` doc page

using https://github.com/huggingface/doc-builder/pull/420


https://moon-ci-docs.huggingface.co/docs/text-generation-inference/pr_1076/en/basic_tutorials/launcher

<img width="800" alt="image"
src="https://github.com/huggingface/text-generation-inference/assets/11827707/cb240198-411f-4d22-9f6e-8f70f2c6dcab">

Adding a new line to escape between heading and codeblock. However, it
is a hotfix and I will work on a permanent solution on
https://github.com/huggingface/doc-builder

I had to open this PR since I initially worked from my fork, and it
requires a handful of work to trigger a new github action on my fork's
specific branch (couldn't find a way, at least, despite trying all of
them).

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

# What does this PR do?

Upgrade all relevant versions and dependencies.

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## Before submitting
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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>

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>

cc @osanseviero

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

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?

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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).
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      Pull Request section?
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Co-authored-by: Lucain <lucainp@gmail.com>
Co-authored-by: Omar Sanseviero <osanseviero@gmail.com>

cc @osanseviero

Added docs for CLI