Datasets:
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83a780e | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 | # Code and Checkpoint Usage
## Code Snapshot
The code archive contains two trees:
- `TwoFrame`: experiment orchestration, evaluation, data-engine scripts, and local project code.
- `FastVideo`: the training stack used for this Wan2.2 fine-tune.
FastVideo matters for this run. The training log references FastVideo modules such as `fastvideo_args.py`, `training_pipeline.py`, and `training_utils.py`. The relevant dirty FastVideo changes are recorded in:
- `metadata/FastVideo.git_status.txt`
- `metadata/FastVideo.uncommitted.diff`
- `metadata/FastVideo.untracked_files.txt`
TwoFrame status is recorded similarly in `metadata/TwoFrame.*`.
## Environment
The UCSF environment used during training was:
```bash
source ~/.twoframe_env.sh
conda activate /scratch/user/yuhwang/envs/twoframe
export PYTHONPATH=/scratch/user/yuhwang/code/FastVideo:/scratch/user/yuhwang/code/TwoFrame:$PYTHONPATH
```
`~/.twoframe_env.sh` points caches and temporary directories to scratch.
## Checkpoints
Use the EMA checkpoint for inference-style evaluation unless you explicitly want non-EMA weights:
- EMA: `checkpoints/ema_checkpoint-8000/diffusion_pytorch_model.safetensors`
- non-EMA: `checkpoints/checkpoint-8000/transformer/diffusion_pytorch_model.safetensors`
Use the distributed checkpoint only if resuming training:
- `checkpoints/checkpoint-8000/distributed_checkpoint/`
## Base Model
The run loaded base model components from:
`/scratch/user/yuhwang/model/Wan2.2-TI2V-5B-Diffusers-merged`
That directory is symlink-composed. Its symlink map is recorded in `metadata/base_model_symlinks.txt`. The base model binaries are not duplicated in this package; this package contains the fine-tuned transformer checkpoint and reproducibility assets.
## Training Command Reconstruction
The exact shell launcher was not preserved in the final run directory. The effective training configuration is captured from the log in `metadata/train_args.json`. Use that file as the source of truth for reconstructing a resume or reproduction launch.
The original output directory was:
`/scratch/user/yuhwang/artifacts/twoframe/pants_wan22_finetune/pants_b16_9k_20260519_215532`
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