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VideoGen-LLM Wan-REPA Adapter Checkpoints
Selected VideoChat2-HD adapter checkpoints from Wan-REPA video understanding experiments.
These are not full base models. They are adapter checkpoints produced by experiments/videochat2_hd_wan_repa_finetune.py and require the corresponding VideoChat2-HD/Mistral setup used in the repository.
Included Checkpoints
| Directory | Setting | Result |
|---|---|---|
eq_seed127_lambda0p1/ |
Equivariance Wan-REPA, seed 127, lambda 0.1 | 49/96 on 5-fold MotionBench subset |
eq_seed123_lambda0p1/ |
Equivariance Wan-REPA, seed 123, lambda 0.1 | 46/96 on 5-fold MotionBench subset |
relation_only/ |
Wan temporal relation alignment, seed 123 | 46/96 on 5-fold MotionBench subset |
Notes
- The full local workspace is on GitHub:
https://github.com/gustn9609/VideoGen-LLM - Base model weights, HDF5 feature caches, and raw videos are not included here.
- The later negative-control and larger-set experiments showed that the Wan-specific gain is weak in the current setup. See
final_summary.mdfor the full interpretation.
Files
adapter_checkpoint.pt: fold-wise adapter/repa-head checkpointfinetune_eval.md: evaluation table for that checkpointsweep_summary.md: seed/lambda robustness summaryfinal_summary.md: final experiment conclusion
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