modelscope / modelscope/DiffSynth-Studio
Reduce the VAP denosing steps
Open
Nobody has claimed this yet.
- Dominant language
- Python
- Stars
- 13.1k
- Forks
- 1.3k
- Avg merge
- 13h 12m
- Merged PRs (30d)
- 45
Description
Denoising 50 steps is too slow. Do you have any good ideas to reduce it? Like some distilled LoRA?
Thanks a lot.
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
The issue identifies VAP denoising as taking 50 steps but names no files, tests, or entry points. Start by locating the VAP denoising implementation and its step configuration, then determine whether an existing distilled LoRA or another supported approach can reduce steps without unacceptable output changes.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- machine-learning, performance
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 20/100