Create README.md

README.md

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+---
+license: apache-2.0
+base_model:
+- Wan-AI/Wan2.1-T2V-1.3B
+- Wan-AI/Wan2.1-T2V-14B
+pipeline_tag: text-to-video
+---
+# rCM: Score-Regularized Continuous-Time Consistency Model
+[**Paper**](https://arxiv.org/abs/2510.08431) | [**Website**](https://research.nvidia.com/labs/dir/rcm) | [**Code**](https://github.com/NVlabs/rcm)
+
+This repo holds converted Wan official checkpoints in rCM/TurboDiffusion style. 
+
+Specifically, rCM equivalently replaces the Conv3d layer in the original Wan with a Linear layer for patch embedding, facilitating further optimization. The layer weight is directly reshaped without value change, e.g., from shape [5120, 16, 1, 2, 2] (Conv3d) to shape [5120, 64] (Linear).
+
+## Citation
+
+```
+@article{zheng2025rcm,
+  title={Large Scale Diffusion Distillation via Score-Regularized Continuous-Time Consistency},
+  author={Zheng, Kaiwen and Wang, Yuji and Ma, Qianli and Chen, Huayu and Zhang, Jintao and Balaji, Yogesh and Chen, Jianfei and Liu, Ming-Yu and Zhu, Jun and Zhang, Qinsheng},
+  journal={arXiv preprint arXiv:2510.08431},
+  year={2025}
+}
+```