modelscope / modelscope/DiffSynth-Studio
Wan2.1 finetuning not considering unconditional training
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- Python
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Description
I'm given to understand that when training a conditional FM/DM the condition (i.e. prompts and referrence images) should be droped with a certain probability (typically 0.5). However I found the Wan finetuning precedure lacks the random dropping part, is there any motivations for this? Any suggestion is appreaciated.
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Research direction
The issue names no file or test; begin by locating the Wan finetuning procedure and reading how prompts and reference images are handled. Compare that behavior with the proposed unconditional-training condition dropping, then establish whether the omission is intentional or define a testable expected behavior before making changes.
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Assessment
- Tech stack
- python
- Domain
- machine-learning
- Issue type
- Bug
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100