linkedin / linkedin/Liger-Kernel
Multi-token attention
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- 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
Hi! Thank you for adding support for MTA (https://github.com/linkedin/Liger-Kernel/pull/689) ! Do I understand it correctly, that this implementation only covers post-sm key-query convolution? There is also pre-sm Q-K convolution, head convolution, and gated group norm (last one should probably not be part of the kernel). We have released reference code here: https://github.com/facebookresearch/RAM/blob/main/projects/mta/mta_transformer.py#L337
### Alternatives
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### Additional context
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Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Read the existing MTA support from PR #689 and compare it with the reference implementation in projects/mta/mta_transformer.py around line 337. Clarify which convolution variants are in scope and whether gated group norm should be excluded; done means the implementation scope is agreed and the selected MTA components are supported.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100