Multi VLLM Worker
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- Dominant language
- Python
- Stars
- 39.5k
- Forks
- 4.8k
- PR merge metrics
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Description
Now that vllm supports llama2 properly, would be awesome to have a peft weight-sharing worker like for regular model serving. The comment at the end of this issue is probably enough to spike one:
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 reviewing FastChat's existing regular model-serving worker and the referenced vLLM issue 182. Determine the required scope for a llama2-compatible PEFT weight-sharing worker and compare it with the current serving design; done means the worker supports the requested multi-worker serving behavior.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- ai, backend
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100