OpenGVLab / OpenGVLab/Ask-Anything
VideoChat2第三阶段的预训练模型使用
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Description
作者好~
在VideoChat2的训练中，
第二阶段训练中，会对Visual Encode和QFormer进行参数训练，导致参数发生变化。
那么在第三阶段训练中，输入的vit_blip_model，是来自于第二阶段参数发生变化的模型，还是重新使用原始的vit_blip_model？
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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.
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Research direction
No file, test, or entry point is named. Start by tracing the VideoChat2 second- and third-stage training configuration, including Visual Encoder, QFormer, and vit_blip_model references. Done means documenting whether stage three uses the modified stage-two model or the original model.
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Assessment
- Tech stack
- python
- Domain
- machine-learning
- Issue type
- Documentation
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 20/100