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but should work on more configurations (no need for 2 GPUs, less RAM
usage).


# What does this PR do?

Reworking the quantization script so it's still universal (not llama
specific)

but should work on more configurations (no need for 2 GPUs, less RAM
usage).

Still need to investigate the potential differences in quantization
results.


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## Before submitting
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      Pull Request section?
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Close #589 #602

![image](https://github.com/huggingface/text-generation-inference/assets/3841370/58177321-479f-4ad1-b3bc-cec027423984)

# What does this PR do?

When passing in environment variables like gptq_bits, we still get
errors thrown from TGI because the try/catch block is catching the wrong
type of error. This PR aims to fix that.

@Narsil - let me know if this is how you want this formatted. My Python
is a little shaky, so I hope this syntax is correct.

- The code is relatively easy (just disable the checks on Embedding and
Head)

This cannot be done in the same easy fashion for hidden_dim/head_dim.
It's relatively easy on some models (classic MHA) but it would make the
other
models (MQA) much more complex, and GPTQ quantization another quite
hairy piece
of code.

# What does this PR do?

This fixes a typo and extends the GPTP_BITS environment variables
through to the second method which requires the same logic. Please let
me know if there's anything I've misunderstood in this change.

Thanks @Narsil for the original fix.

Logger is referenced during the apex importing but is not imported,
causing a NameError

Fixes #541

# What does this PR do?

Some models are already converted, and do not have those values in the
file, this enables users to use them with less friction.

Went for pure env based because adding flags would end up (imo) very
tedious to maintain. There's a lot of sanitation to do: those flags
would be errors if not used in conjuction with `--quantize gptq`.
Then the flags need to exist in the launcher and the server passing them
all throughout all function calls.

This PR is intended as an easy escape hatch, not the defacto method to
use gptq in TGI.

Fixes #500

fix(server): Fixing RW code (it's remote code so the Arch checking doesn't work to see which weights to keep). (#579)

Fixes #555

Close #571

- Look at `transformers` base class to check for
  `_key_to_ignore_on_load_missing` or `_tied_weights` which are the
  standard attributes to select the keys to NOT save on disk (since they
  are ignored)

- Modified safetensors code (to be reflected in safetensors even if it's
  an internal function).
  
- Will not work for trust_remote_code=True repos (like santacoder).

Should help with :
https://github.com/huggingface/text-generation-inference/issues/555
and : https://github.com/huggingface/text-generation-inference/pull/501
and https://github.com/huggingface/text-generation-inference/issues/556
and
https://github.com/huggingface/text-generation-inference/issues/482#issuecomment-1623713593

# What does this PR do?

In title. Adds argument `--hostname` in router to support something like
`--hostname ::`. Tested with

```commandline
cargo run -- --port 8080 --hostname ::
curl -I -X GET 'http://[::1]:8080/health

'  # failed before this commit
```

Trigger CI

---------
Co-authored-by: Phil Chen <philchen2000@gmail.com>

@njhill FYI

See https://github.com/huggingface/transformers/pull/24111

I didn't add validation to the `__init__` method since it's not done for
other values/warpers.

This PR allows the MPT model to be loaded from local files. Without this
change, an exception will be thrown by `hf_hub_download` function if
`model_id` is a local path.

# What does this PR do?

For consistency and ease of use (you can just run `make` to install vllm
without any extra steps).

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## Before submitting
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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
[documentation
guidelines](https://github.com/huggingface/transformers/tree/main/docs),
and
[here are tips on formatting
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- [ ] Did you write any new necessary tests?


## Who can review?

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passed. Feel free to tag
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# What does this PR do?


This adds a non flash version of MPT.
Flash is harder because we need to create a bias ready cuda kernel of
flash attention.

Fixes
https://github.com/huggingface/text-generation-inference/issues/361
Fixes
https://github.com/huggingface/text-generation-inference/issues/491
Fixes
https://github.com/huggingface/text-generation-inference/issues/290

Closes #478

# This PR adds an http header option to disable buffering for the
generate_stream endpoint response stream.

Problem: If a model is run behind a proxy server such as nginx that has
buffering enabled then the response stream from generate_stream gets
aggregated into a single response which basically disables streaming.
Instead of getting a chunked response where each token is presented over
time the response presents everything all at once.

Solution: This change adds the `X-Accel-Buffering` http header which
disables buffering for the generate_stream response, allowing the
response to stream properly.