OpenGVLab / OpenGVLab/InternVideo

Consider using pre-built Flash Attention kernels via `kernels`

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Dominant language
Python
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Description

Hey,

I am Sayak from the Kernels team at Hugging Face. I noticed that this project uses Flash Attention which includes a long build time. We ship pre-built binaries (which provide bit-exact outputs as the upstream) and thereby, we make it easy to use.

Using FA3 on a supported machine is as easy as:

# make sure `kernels` is installed: `pip install -U kernels`
from kernels import get_kernel

kernel_module = get_kernel("kernels-community/flash-attn3")
flash_attn_func = kernel_module.flash_attn_func

flash_attn_func(...)

Let us know if you'd be interested in this and and we'd be happy to provide a draft of how it would look in your repo.

Contributor guide

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First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

Research direction

Locate the repository's current Flash Attention integration and identify where its build and runtime dependency are configured. Compare that path with the kernels installation and get_kernel("kernels-community/flash-attn3") example in the issue. Done should mean a maintainable decision or working integration with supported-machine behavior and equivalent outputs verified.

Written by the indexing model from the issue text.

Assessment

Tech stack
python
Domain
machine-learning, performance
Issue type
Feature
Difficulty
4/5
Estimated time
3-5 days
Activity status
Active
Clarity
Needs clarification
Newbie friendliness
35/100

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