modelscope / modelscope/DiffSynth-Studio
Is it reasonable to train the low_noise part and high_noise part of Wan2.2 separately?
Nobody has claimed this yet.
- Dominant language
- Python
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Description
I think training the two parts of parameters separately will lead to incompatibility during inference.
I guess the original training of Wan2.2 should have been conducted with both parts together?
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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 referenced entry point is examples/wanvideo/model_training/lora/Wan2.2-I2V-A14B.sh; read it first to see how the low_noise and high_noise parts are selected during training. Check the Wan2.2 training assumptions and determine whether separate training is supported or joint training is required; done means a confirmed compatibility answer and any needed documentation update.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python, shell
- Domain
- ai, machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100