GitLab

* Adding Service Name Environment variable for https://github.com/huggingface/text-generation-inference/issues/2069

* Update Docs

* Update README.md

* Update Launcher Docs

* Update Launcher Docs
Removing Option

* Support HF_TOKEN environement variable

* Load test.

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

* Fix cargo-chef prepare

In prepare stage, cargo-chef reads Cargo.lock and transforms it accordingly.
If Cargo.lock is not present, cargo-chef will generate a new one first, which
might vary a lot and invalidate docker build caches.

* Fix Dockerfile_amd and Dockerfile_intel

* New runner. Manual squash.

* Network host.

* Put back trufflehog with proper extension.

* No network host ?

* Moving buildx install after tailscale ?

* 1.79

The subcommand did not work due to some broken imports.

For Phi-3-Small I need to shard a packed QKV bias tensor, for which
I implemented the `Weights.get_packed_sharded` method. However, this
method can also replace the `Weights._get_qweight` method and the
custom sharding code from `Weights.get_weights_col_packed`.

Fixes #2081.

* test local tailscale

* Update build.yaml

* Update build.yaml

* Update build.yaml

* Update build.yaml

* wait for ssh

* network host

* change step order

* Set maximum grpc message receive size to 2GiB

The previous default was 4MiB, which doesn't really work well for
multi-modal models.

* Update to Rust 1.79.0

* Fixup formatting to make PR pass

* Contributing guide & Code of Conduct

* Redirect to GitHub's tutorial on PRs

When a batch contained images if different sizes during prefill, the
server would fail (see e.g. #2056). Images were processed separately and
then concatenated. However, this can fail for images with different sizes.

Fix this by preprocessing all images in the batch together, so that the
image processor can ensure that all image tensors have compatible sizes.

* doc: adding architecture document

* doc: add architecture to toctree

* fix: avoid cargo lock changes

* fix: avoid cargo lock tweak

---------
Co-authored-by: drbh <david.richard.holtz@gmail.com>

* Update the link for qwen2

* Fix Qwen2 model URL in model table

* Fix too eager staging

---------
Co-authored-by: Daniël de Kok <me@danieldk.eu>

Add support for GPTQ Marlin kernels

GPTQ Marlin extends the Marlin kernels to support common GPTQ
configurations:

- bits: 4 or 8
- groupsize: -1, 32, 64, or 128
- desc_act: true/false

Using the GPTQ Marlin kernels requires repacking the parameters in the
Marlin quantizer format.

The kernels were contributed by Neural Magic to VLLM. We vendor them
here for convenience.

* feat: add kserve feature and basic routes

* feat: implement infer endpoint wrapper around generate

* fix: refactor and improve types

* fix: improve infer and simplify

* fix: cleanup and improve api docs

* fix: refactor and encapsulate kserve feat in file

* fix: remove typos after rebase

* Use minijinja's pycompat mode for python methods

* fix: cargo fmt lint for pre commit

---------
Co-authored-by: Armin Ronacher <armin.ronacher@active-4.com>

* fix(layers): fix SuRotaryEmbedding

* change arange

* remove logs

* feat: support response_format in chat

* fix: adjust typos

* fix: add trufflehog lint

update commit

Add support for Phi-3-medium

The main difference between the medium and mini models is that medium
uses grouped query attention with a packed QKV matrix. This change adds
support for GQA with packed matrixes to `Weights.get_weights_col_packed`
and uses it for Phi-3. This also allows us to remove the custom
implementation of GQA from dbrx attention loading.

* update vllm commit & fix models using sliding window

* update

* update commit

* fix bug where tunableop is bound to cuda graph even when cuda graph are disabled

* enable tunableop by default

* fix sliding window

* address review

* dead code

* precise comment

* is it flaky?

The router will now send the input as chunks besides as a single
string. This change modifies the server to process chunked input
rather than strings. This also allows us to remove the image
extraction code from the server.

# What does this PR do?

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

This reverts commit 101ac9a7.

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This change adds support for Marlin-quantized models. Marlin is an
FP16xINT4 matmul kernel, which provides good speedups decoding batches
of 16-32 tokens. It supports quantized models with symmetric
quantization, groupsize -1 or 128, and 4-bit.

Tested with:

- Llama 2
- Llama 3
- Phi 3

This reverts commit 5aec4154.

There was a new release of the python client with version upped to 0.7.0
on pip and on the pyproject.toml, but it wasn't changed on the
__init__.py so when one does:

```python
import text_generation
print(text_generation.__version__)
```

It still outputs "0.6.0"

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# What does this PR do?

Fix stray import.

## 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?
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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
docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation).
- [ ] Did you write any new necessary tests?


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