GitLab

This PR addresses an issue where calling `model = model.cuda()` would
throw a ValueError when `quantize` is set to "bitsandbytes".

```
> File "/opt/conda/lib/python3.9/site-packages/text_generation_server/server.py", line 147, in serve_inner
    model = get_model(
  File "/opt/conda/lib/python3.9/site-packages/text_generation_server/models/__init__.py", line 295, in get_model
    return CausalLM(
  File "/opt/conda/lib/python3.9/site-packages/text_generation_server/models/causal_lm.py", line 515, in __init__
    model = model.cuda()
  File "/opt/conda/lib/python3.9/site-packages/transformers/modeling_utils.py", line 1998, in cuda
    raise ValueError(
ValueError: Calling `cuda()` is not supported for `4-bit` or `8-bit` quantized models. Please use the model as it is, since the model has already been set to the correct devices and casted to the correct `dtype`.
```
Co-authored-by: mmnga <mmnga1mmnga@gmail.com>

Fixes a link in doc

# What does this PR do?

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# 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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# What does this PR do?

Now clients which do not specify a max_length will be implying
`max_new_tokens = max_total_tokens - input_length`.
This is a serious change, but which seems more in line with what users
expect from standing server.

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---------
Co-authored-by: OlivierDehaene <olivier@huggingface.co>

# What does this PR do?

Fix #1095

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Just removed `--` from the arguments. 
With `--` bitsandbytes and bitsandbytes-nf4 are considered an option
which they are not

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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">

# What does this PR do?
This PR is meant to handle cases in which the images provided are
invalid.

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@Narsil

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

This fixes flash attention v1 which was always
NotImplementedError("window_size_left is only available with flash attn
v2").

Currently flash_llama_modeling.py doesn't override the default value of
window_size_left when calling attention(..) (line 282). This means that
window_size_left will always be the default of -1, but flash attention
v1 throws an exception if `window_size_left != 0`.

To fix this, we should be checking `window_size_left != -1` before
throwing the NotImplementedError.


Fixes #1084 


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# What does this PR do?

Fixes #1079 
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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?

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`FastLinear.load` requires 4 parameters, but in the following only 3 are
given. This PR fix this.

```python
# server/text_generation_server/models/custom_modeling/opt_modeling.py
        if config.word_embed_proj_dim != config.hidden_size:
            self.project_out = FastLinear.load(
                config, prefix="model.decoder.project_out", bias=False
            )
        else:
            self.project_out = None

        if config.word_embed_proj_dim != config.hidden_size:
            self.project_in = FastLinear.load(
                config, prefix="model.decoder.project_in", bias=False
```

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Superseed #1024


# 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: bangoz <ch_xie@pku.edu.cn>

# What does this PR do?

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Fixes # (issue)


## Before submitting
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other checks if that's the case).
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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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---------
Co-authored-by: zhaosida <zhaosida@corp.netease.com>

Added note on serving supported models from a different folder without
re-downloading 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
- [ ] This PR fixes a typo or improves the docs (you can dismiss the
other checks if that's the case).
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guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests),
      Pull Request section?
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      to it if that's the case.
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# What does this PR do?

I made an embarrassing mistake where I accidentally passed normal
softmax probabilities into `batch_top_tokens` for `CausalLM` and
`Seq2SeqLM`.

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## 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?

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@Narsil

Problem and fix is described here:
https://huggingface.co/HuggingFaceM4/idefics-9b/discussions/9



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

# What does this PR do?

Install curl within base image, negligible regarding the image volume
and will allow to easily perform a better health check. Not sure about
the failing github actions though. Should I fix something ?
Signed-off-by: Raphael <oOraph@users.noreply.github.com>
Co-authored-by: Raphael <oOraph@users.noreply.github.com>

# What does this PR do?

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Model Class attributes `_tied_weights_keys`, `
_keys_to_ignore_on_load_missing` can only be `None` or a List.
`getattr(class_, "_keys_to_ignore_on_load_missing", [])` will return
`None` if `_keys_to_ignore_on_load_missing` is None, and
`discard_names.extend(None)` will trigger an exception, even though
`_tied_weights_keys` exists.

## Who can review?

@OlivierDehaene  @Narsil

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

# What does this PR do?

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Support local config file to avoid unexpected `discard_names`, which
causes #1057.

In the case of launching local mode without `model.safetensors` file,
the original code will result `discard_names = []` when
`hf_hub_download` throws an connection error.
```python
# server/text_generation_server/cli.py
    try:
        import transformers
        import json
    
    
        config_filename = hf_hub_download(model_id, revision=revision, filename="config.json")
        with open(config_filename, "r") as f:
            config = json.load(f)
        architecture = config["architectures"][0]
    
        class_ = getattr(transformers, architecture)
    
        # Name for this varible depends on transformers version.
        discard_names = getattr(class_, "_tied_weights_keys", [])
        discard_names.extend(getattr(class_, "_keys_to_ignore_on_load_missing", []))
    
    except Exception as e:
        discard_names = []
```

The expected `_tied_weights_keys` of OPT-1.3b is `["lm_head.weight"]`,
and its tied weight `"model.decoder.embed_tokens.weight"` will be kept
in the safetensors conversion. But the above empty `discard_names` will
lead to `"lm_head.weight"` being kept and
`"model.decoder.embed_tokens.weight"` being discard in the subsequent
method `_remove_duplicate_names`, which causes error #1057.

So add a local mode branch to get the expected `discard_names` like
follows. This modification also applies to other models

```python
# server/text_generation_server/cli.py
        if is_local_model:
            config_filename = os.path.join(model_id, "config.json")
        else:
            config_filename = hf_hub_download(model_id, revision=revision, filename="config.json")
```


In addition, when `_tied_weights_keys` or
`_keys_to_ignore_on_load_missing` is `None`, the above code will also
throw an error unexpectedly. This is fixed in PR #1052


## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the
other checks if that's the case).
- [x] Did you read the [contributor
guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests),
      Pull Request section?
- [x] 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).
N/A
- [ ] Did you write any new necessary tests?  N/A


## Who can review?

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passed. Feel free to tag
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@Narsil

# 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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## 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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      to it if that's the case.
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- [ ] Did you write any new necessary tests?


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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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## Before submitting
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other checks if that's the case).
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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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- [ ] Did you write any new necessary tests?


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