modelscope / modelscope/DiffSynth-Studio
[FETAURE] Add WAN Vace LoRA train with full dataset
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Description
I want to train LoRA for Vace version of WAN2.2.
My main task is make stable video outpainting.
So, I have dataset data
cropped.mp4 - cropped video with grey border.
mask.mp4 - video, where every frame is mask
orig.mp4 - original video to compare output
description.txt - text file with positive prompt
Dataset arch:
- <root_dir>
-- <video_guid>
---- cropped.mp4
---- mask.mp4
---- orig.mp4
---- description.txt
-- <video_guid>
---- cropped.mp4
---- mask.mp4
---- orig.mp4
---- description.txt
How can I train LoRA for Vace layers with full dataset?
Model for ex.: https://huggingface.co/linoyts/Wan2.2-VACE-Fun-14B-diffusers
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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 requested Wan2.2-VACE-Fun-14B-diffusers model and the dataset files cropped.mp4, mask.mp4, orig.mp4, and description.txt. Determine how the existing training workflow handles the full dataset layout and VACE layers; done means a defined, supported way to train the requested LoRA for stable video outpainting.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- 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