aigc-apps / aigc-apps/VideoX-Fun
Minimax PDD Distillation
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- Dominant language
- Python
- Stars
- 2.3k
- Forks
- 188
- Avg merge
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- Merged PRs (30d)
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Description
Great job on the LoRA! The best out so far for sure!
I also played around with PDD a bit but never managed to reproduce the results from the paper. Do you have any insights into the algorithm, which hyperparameters matter the most etc?
Sharing your setup would be amazing!
Thanks!
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
The issue names no files, tests, or entry points. First read the PDD paper and compare its algorithm, hyperparameters, and setup with the repository’s Minimax/PDD implementation; done means documenting a reproducible setup and the settings that matter most.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- ai, machine-learning
- Issue type
- Documentation
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Active
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100