* 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
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.
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
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.
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Signed-off-by: Wang, Yi A <yi.a.wang@intel.com>
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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
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"
# What does this PR do?
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# What does this PR do?
Fix stray import.
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# What does this PR do?
Do not attempt to allocate ExLlamaV2 scratch buffers when there are no
ExLlama2 layers. Avoids a crash in warmup for models that cannot use
exllama when ExLlamaV2 is installed.
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# What does this PR do?
Fixes initial and subsequent installs (protection for folder creation
should only be for git commit, checking out correct commit should be on
both.
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# What does this PR do?
Making `make install` a much better sane default to start local dev
environments.
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# What does this PR do?
The GPTQ code path for column-packed packed tensors assumed that this is
always a QKV matrix. However, models (e.g. Phi-3) can also have
column-packed MLP up/gate matrices.
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- Refactor code to allow supporting multiple versions of the
generate.proto at the same time
- Add v3/generate.proto (ISO to generate.proto for now but allow for
future changes without impacting v2 backends)
- Add Schedule trait to abstract queuing and batching mechanisms that
will be different in the future
- Add SchedulerV2/V3 impl
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PR #1986 moved the location of the `flash_attn_triton.py` file. This PR
adjusts sources to changes.
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Signed-off-by: Emmanuel Ferdman <emmanuelferdman@gmail.com>
# What does this PR do?
We were using the wrong parallelism in the up-projection.
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Before this change, the generation input was sent to the backend as a
single string, encoding images as Base64 and packing them in
Markdown-style links.
This change adds a new chunked input representation that separates text
chunks from images chunks. Image chunks contain binary data (for smaller
message sizes) and the image's MIME type.
The stringly-typed inputs are still sent to support backends that do not
support chunked inputs yet.
# What does this PR do?
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---------
Signed-off-by: Wang, Yi A <yi.a.wang@intel.com>
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# 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).
- [ ] 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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