Wan 2.1 Fun Reward LoRAs

--- license: apache-2.0 language: - en - zh pipeline_tag: text-to-video library_name: videox_fun tags: - video - video-generation --- # Wan2.1-Fun-Reward-LoRAs ## Introduction We explore the Reward Backpropagation technique ^{[1](#ref1) [2](#ref2)} to optimized the generated videos by [Wan2.1-Fun](https://github.com/aigc-apps/VideoX-Fun) for better alignment with human preferences. We provide the following pre-trained models (i.e. LoRAs) along with [the training script](https://github.com/aigc-apps/VideoX-Fun/blob/main/scripts/wan2.1_fun/train_reward_lora.py). You can use these LoRAs to enhance the corresponding base model as a plug-in or train your own reward LoRA. For more details, please refer to our [GitHub repo](https://github.com/aigc-apps/VideoX-Fun). | Name | Base Model | Reward Model | Hugging Face | Description | |--|--|--|--|--| | Wan2.1-Fun-1.3B-InP-HPS2.1.safetensors | [Wan2.1-Fun-1.3B-InP](https://huggingface.co/alibaba-pai/Wan2.1-Fun-1.3B-InP) | [HPS v2.1](https://github.com/tgxs002/HPSv2) | [🤗Link](https://huggingface.co/alibaba-pai/Wan2.1-Fun-Reward-LoRAs/resolve/main/Wan2.1-Fun-1.3B-InP-HPS2.1.safetensors) | Official HPS v2.1 reward LoRA (`rank=128` and `network_alpha=64`) for Wan2.1-Fun-1.3B-InP. It is trained with a batch size of 8 for 5,000 steps.| | Wan2.1-Fun-1.3B-InP-MPS.safetensors | [Wan2.1-Fun-1.3B-InP](https://huggingface.co/alibaba-pai/Wan2.1-Fun-1.3B-InP) | [MPS](https://github.com/Kwai-Kolors/MPS) | [🤗Link](https://huggingface.co/alibaba-pai/Wan2.1-Fun-Reward-LoRAs/resolve/main/Wan2.1-Fun-1.3B-InP-MPS.safetensors) | Official MPS reward LoRA (`rank=128` and `network_alpha=64`) for Wan2.1-Fun-1.3B-InP. It is trained with a batch size of 8 for 7,500 steps.| | Wan2.1-Fun-14B-InP-HPS2.1.safetensors | [Wan2.1-Fun-14B-InP](https://huggingface.co/alibaba-pai/Wan2.1-Fun-14B-InP) | [HPS v2.1](https://github.com/tgxs002/HPSv2) | [🤗Link](https://huggingface.co/alibaba-pai/Wan2.1-Fun-Reward-LoRAs/resolve/main/Wan2.1-Fun-14B-InP-HPS2.1.safetensors) | Official HPS v2.1 reward LoRA (`rank=128` and `network_alpha=64`) for Wan2.1-Fun-14B-InP. It is trained with a batch size of 32 for 3,000 steps.| | Wan2.1-Fun-14B-InP-MPS.safetensors | [Wan2.1-Fun-14B-InP](https://huggingface.co/alibaba-pai/Wan2.1-Fun-14B-InP) | [MPS](https://github.com/Kwai-Kolors/MPS) | [🤗Link](https://huggingface.co/alibaba-pai/Wan2.1-Fun-Reward-LoRAs/resolv...