linkedin / linkedin/Liger-Kernel

MoE kernel

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feature
Dominant language
Python
Stars
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Forks
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Avg merge
1d 20h
Merged PRs (30d)
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Description

### 🚀 The feature, motivation and pitch

Currently the most popular library might be https://github.com/databricks/megablocks. Would be interesting if we can implement it in triton and make it HF compatible

### Alternatives

_No response_

### Additional context

_No response_

Contributor guide

Open the contributing guide

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

The issue names no files, tests, or entry points. Start by comparing the requested Triton implementation with Megablocks and clarify the expected Hugging Face compatibility; done would require an agreed MoE kernel implementation and validation criteria.

Written by the indexing model from the issue text.

Assessment

Tech stack
huggingface, python
Domain
machine-learning, performance
Issue type
Feature
Difficulty
5/5
Estimated time
Over a week
Activity status
Stale
Clarity
Needs clarification
Newbie friendliness
25/100

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