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| File | Description |
|---|---|
adapter_model.bin | PEFT LoRA weights (rank 256, targets CausalWanAttentionBlock) |
adapter_config.json | LoRA configuration |
1git clone https://github.com/h6kplus/PhyMotion.git
2cd PhyMotion
3
4# Download this LoRA adapter
5huggingface-cli download 6kplus/PhyMotion-CausalForcing-1.3B \
6 --local-dir checkpoints/phymotion-causalforcing
7
8# Download MotionX prompts (train + test)
9huggingface-cli download 6kplus/PhyMotion-MotionX-Prompts \
10 --repo-type dataset --local-dir dataset/motionx
11
12# Inference
13# Note: You still need the base Causal Forcing 1.3B checkpoint (causal_forcing.pt)
14torchrun --nproc_per_node=1 scripts/inference_wan.py \
15 --base_model checkpoints/causalforcing/chunkwise/causal_forcing.pt \
16 --lora_path checkpoints/phymotion-causalforcing \
17 --prompt_file dataset/motionx/test.txt \
18 --output_dir outputs/test \
19 --num_frames 45 --height 480 --width 832 \
20 --guidance_scale 3.0 \
21 --denoising_steps "1000,750,500,250" \
22 --num_frame_per_block 3 \
23 --mixed_precision bf16 --seed 421@article{huang2026phymotion,
2 title = {PhyMotion: Structured 3D Motion Reward for Physics-Grounded Human Video Generation},
3 author = {Huang, Yidong and Wang, Zun and Lin, Han and Kim, Dong-Ki and
4 Omidshafiei, Shayegan and Yoon, Jaehong and Cho, Jaemin and
5 Zhang, Yue and Bansal, Mohit},
6 journal = {arXiv preprint arXiv:2605.14269},
7 year = {2026}
8}