OptimalScale / OptimalScale/LMFlow
LoRA + FlashAttention2 speed up？
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- Dominant language
- Python
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- 8.5k
- Forks
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Description
When fine-tuning Mistral with LoRA, do you think FlashAttention2 helps in speeding up the process? If yes, how significant is the acceleration? Where is the primary acceleration achieved?
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
No files, tests, or entry points are named. Start by locating the Mistral LoRA fine-tuning path and the FlashAttention2 configuration, then benchmark comparable runs to measure overall and component-level acceleration; document the results and explanation.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python, pytorch
- Domain
- machine-learning, performance
- Issue type
- Documentation
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 15/100