| language: | |
| - en | |
| pipeline_tag: text-to-video | |
| tags: | |
| - video-generation | |
| - autoregressive | |
| - wan | |
| - rmd | |
| base_model: | |
| - Wan-AI/Wan2.1-T2V-1.3B | |
| - Wan-AI/Wan2.1-T2V-14B | |
| # RMD: Rollout-Marginal Distillation | |
| **Train on 5 seconds. Generate far beyond.** | |
| Pretrained weights for long-horizon autoregressive video generation with a | |
| four-step causal Wan 1.3B model. | |
| ## Weights | |
| | File | Purpose | | |
| | --- | --- | | |
| | `stage2/model.pt` | Final model for inference (5.68 GB) | | |
| | `stage1/model.pt` | Stage 1 model / initialization for stage 2 | | |
| | `training/fake_score.pt` | Adapted fake-score initialization | | |
| | `training/teacher_lora/adapter_model.bin` | Wan 14B teacher LoRA | | |
| ## Download | |
| ```bash | |
| hf download cjeen/RMD stage2/model.pt --local-dir checkpoints/rmd | |
| ``` | |
| Inference also needs the [Wan 1.3B assets](https://huggingface.co/Wan-AI/Wan2.1-T2V-1.3B). | |
| These checkpoints use the RMD code, not a standalone Diffusers pipeline. | |
| See the [quick start](https://github.com/cjeen/RMD#quick-start) for generation | |
| and the [training guide](https://github.com/cjeen/RMD#train-rmd) | |
| for training. Causal ODE initialization is downloaded separately from | |
| [Causal Forcing](https://huggingface.co/zhuhz22/Causal-Forcing). | |
| Upstream model and initialization licenses still apply; `CODE_LICENSE` covers | |
| the source code only. File checksums are listed in `manifest.json`. | |