| --- |
| license: apache-2.0 |
| base_model: |
| - Wan-AI/Wan2.1-T2V-1.3B |
| - Wan-AI/Wan2.1-T2V-14B |
| tags: |
| - video-generation |
| - autoregressive |
| - text-to-video |
| --- |
| |
| # 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). |
|
|
| ```bash |
| # 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. |
| |
