sgl-project / sgl-project/SpecForge
[Feature] VLM model support flex attention
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- Dominant language
- Python
- Stars
- 1.2k
- Forks
- 347
- Avg merge
- 4d 1h
- Merged PRs (30d)
- 41
Description
Checklist
- 1. If the issue you raised is not a feature but a question, please raise a discussion at https://github.com/sgl-project/SpecForge/discussions/new/choose Otherwise, it will be closed.
- 2. Please use English, otherwise it will be closed.
Motivation
VLM model support flex attention
Related resources
No response
Contributor guide
No contributing guide indexed for this repository
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
Start by locating the existing VLM model support and the attention implementation in SpecForge. Determine which VLM models are in scope and how flex attention should integrate with them. Done should include defined model coverage, implementation, and tests demonstrating that supported VLM models work with flex attention.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python, pytorch
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100