GitLab

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>

# What does this PR do?

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This PR adds the possibility to run AWQ models with Exllama/GPTQ
kernels, specifically for ROCm devices that support Exllama kernels but
not AWQ's GEMM.

This is done by :
- un-packing, reordering and re-packing AWQ weights when `--quantize
gptq` but the model's `quant_method=awq`.
- avoiding overflows when adding 1 to zeros in exllama and triton.

Ref: https://github.com/casper-hansen/AutoAWQ/pull/313

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

# What does this PR do?

Superseeds #1459

The fix works as follows.
We updated next_token_chooser to return all logprbs, then
batch_top_n_tokens, now also gets accepted_ids + speculated_length (so
it knows how to interpret the flat logprobs).

We then update the code to return lists ot `Tokens` that it expects.
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Tested with
```
CUDA_VISIBLE_DEVICES=0 text-generation-launcher --model-id TheBloke/Llama-2-7B-Chat-GPTQ --quantize gptq
EXLLAMA_VERSION=1 CUDA_VISIBLE_DEVICES=0 text-generation-launcher --model-id TheBloke/Llama-2-7B-Chat-GPTQ --quantize gptq
CUDA_VISIBLE_DEVICES="0,1" text-generation-launcher --model-id TheBloke/Llama-2-7B-Chat-GPTQ --quantize gptq
```

all with good and identical results on MI210.

---------
Co-authored-by: Felix Marty <felix@hf.co>
Co-authored-by: OlivierDehaene <olivier@huggingface.co>
Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com>

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local directory overloaded still needs the directory to locate the
weights files correctly.

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

Works by removing adapter_model.safetensors from being detected as the
core model file (which skips the real peft detection).

# What does this PR do?

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@oOraph

---------
Signed-off-by: Raphael Glon <oOraph@users.noreply.github.com>
Co-authored-by: Raphael Glon <oOraph@users.noreply.github.com>

This PR adds support for AMD Instinct MI210 & MI250 GPUs, with paged
attention and FAv2 support.

Remaining items to discuss, on top of possible others:
* Should we have a
`ghcr.io/huggingface/text-generation-inference:1.1.0+rocm` hosted image,
or is it too early?
* Should we set up a CI on MI210/MI250? I don't have access to the
runners of TGI though.
* Are we comfortable with those changes being directly in TGI, or do we
need a fork?

---------
Co-authored-by: Felix Marty <felix@hf.co>
Co-authored-by: OlivierDehaene <olivier@huggingface.co>
Co-authored-by: Your Name <you@example.com>

# What does this PR do?

See #1165

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---------
Co-authored-by: Florian Zimmermeister <flozi00.fz@gmail.com>
Co-authored-by: Ubuntu <ubuntu@ip-172-31-24-153.ec2.internal>

Peft loading function was missing the
`trust_remote_code=trust_remote_code` argument causing the custom
tokenizer code to be not found.


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@Narsil

# What does this PR do?


Fixes #1017

Not sure if there's a mistake here but 

- NousResearch/Yarn-Llama-2-7b-128k seems to be working fine
- TheBloke/Yarn-Llama-2-13B-128K-GPTQ outputs garbage



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# What does this PR do?

Fixes #1098 
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# What does this PR do?
Fixing a list type hint definition (I believe this was a typo).

Allows backward compatibility with Python 3.8 (relevant for
JetPack-enabled systems).

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