RVC-Project / RVC-Project/Retrieval-based-Voice-Conversion-WebUI
Perform Model Distillation on Pretrained models for faster inference
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- Python
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Description
recently some papers claims to have achieved a great infer performance improvement by distillation technique (on so-vitis), I was thinking that this could be applied to RVC's pretrained as well
link to Distillation paper -> https://arxiv.org/abs/2401.01792
link to paper's code -> https://github.com/Grace9994/CoMoSVC.git
Contributor guide
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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 the linked Distillation paper and its CoMoSVC code, then trace how RVC's pretrained models are loaded and used for inference. The issue does not identify files, tests, target models, or measurable inference goals, so completion criteria would need to be defined before implementation.
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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
- 20/100