aigc-apps / aigc-apps/VideoX-Fun
How to train a customized Cogvideox-fun-v1.1-5b-control model based on CogVideoX-Fun-V1.1-5b-InP weights?
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Description
Hi! I am looking to train a customized controlled video generation model using specific control data types (e.g., normal maps or optical flow).
The released pre-trained model has been trained on non-target control types. I aim to leverage CogVideoX-Fun-V1.1-5b-InP model's weights and perform training based on the framework of CogVideoX-Fun-V1.1-5b-Control.
How can I achieve this using the provided training code? Any advice would be greatly appreciated.
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Research direction
Start with the provided training code and the CogVideoX-Fun-V1.1-5b-Control and CogVideoX-Fun-V1.1-5b-InP weights named in the issue. Trace how the training code loads weights and handles control data types such as normal maps or optical flow. Done means a documented, reproducible procedure for training the customized model.
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Assessment
- Tech stack
- python
- Domain
- machine-learning
- Issue type
- Documentation
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 20/100