illustro1/clean-forcing

Clean Forcing — adapted base checkpoints

Checkpoints for Clean Forcing: Drift-Resistant Autoregressive Video Diffusion with a Frozen Base: the causally adapted Wan2.1 bases (repo root) and the 14 drift-corrector LoRAs (weights/, rank 16 on self-attention q/k/v/o; weights/README.md maps each LoRA to its base and paper row).

# from the code repo root: LoRAs land in weights/, bases in the repo root
huggingface-cli download illustro1/clean-forcing --local-dir .
mv adapted_base_4000.pt self_forcing/wan_cache/

File	Base	Size	Used for
adapted_base_4000.pt	Wan2.1-T2V-1.3B + rank-64 causal adapter (merged, step 4K)	0.57 GB	all 1.3B results (Table 1 and ablations)
wan14b_adapted_base_4000.pt	Wan2.1-T2V-14B + rank-64 causal adapter (merged, step 4K)	8.4 GB	the 14B scale-transfer appendix

Load the merged weights with torch.load(path)["merged"] into the block-causal pipeline (see the code repo's RUN.md). Verify downloads with sha256sum -c SHA256SUMS (bases) and cd weights && sha256sum -c SHA256SUMS (LoRAs).

• Code: https://github.com/wnqw/clean_forcing
• Project page and paper: https://clean-forcing.github.io/

Both checkpoints are derived from Wan2.1 (Apache-2.0) and are released under the same license.