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README.md
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base_model:
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- Wan-AI/Wan2.1-T2V-14B
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pipeline_tag: text-to-video
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base_model:
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- Wan-AI/Wan2.1-T2V-14B
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pipeline_tag: text-to-video
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---
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<div align="center">
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<h1>
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Wan-Alpha
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</h1>
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<h3>Wan-Alpha: High-Quality Text-to-Video Generation with Alpha Channel</h3>
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[](https://arxiv.org/abs/)
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[](https://www.xxxx)
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[](https://huggingface.co/xxxx)
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</div>
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<img src="assets/teaser.png" alt="Wan-Alpha Qualitative Results" style="max-width: 100%; height: auto;">
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>Qualitative results of video generation using **Wan-Alpha**. Our model successfully generates various scenes with accurate and clearly rendered transparency. Notably, it can synthesize diverse semi-transparent objects, glowing effects, and fine-grained details such as hair.
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---
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## 🔥 News
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* **[2025.09.30]** Released Wan-Alpha v1.0, the Wan2.1-14B-T2V–adapted weights and inference code are now open-sourced.
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---
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## 🌟 Showcase
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### Text-to-Video Generation with Alpha Channel
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## 🌟 Showcase
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### Text-to-Video Generation with Alpha Channel
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<!-- | Prompt | Generated Video | Alpha Video |
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| :---: | :---: | :---: |
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| "Medium shot. A little girl holds a bubble wand and blows out colorful bubbles that float and pop in the air. The background of this video is transparent. Realistic style." |
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<div style="display: flex; gap: 10px;">
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<img src="girl.gif" alt="..." style="flex: 1; min-width: 200px;">
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</div> |
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<div style="display: flex; gap: 10px;">
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<img src="girl_pha.gif" alt="..." style="flex: 1; min-width: 200px;">
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</div> | -->
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| Prompt | Generated Video | Alpha Video |
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| :---: | :---: | :---: |
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| "Medium shot. A little girl holds a bubble wand and blows out colorful bubbles that float and pop in the air. The background of this video is transparent. Realistic style." | <img src="assets/girl.gif" width="320" height="180" style="object-fit:contain; display:block; margin:auto;"/> | <img src="assets/girl_pha.gif" width="320" height="180" style="object-fit:contain; display:block; margin:auto;"/> |
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### For more results, please visit [https://Wan-Alpha.github.io/](https://www.xxx)
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## 🚀 Quick Start
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### 1. Environment Setup
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```bash
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# Clone the project repository
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git clone https://github.com/WeChatCV/Wan-Alpha.git
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cd Wan-Alpha
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# Create and activate Conda environment
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conda create -n Wan-Alpha python=3.11 -y
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conda activate Wan-Alpha
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# Install dependencies
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pip install -r requirements.txt
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```
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### 2. Model Download
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Download [Wan2.1-T2V-14B](https://huggingface.co/Wan-AI/Wan2.1-T2V-14B)
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Download [Lightx2v-T2V-14B](https://huggingface.co/Kijai/WanVideo_comfy/blob/main/Lightx2v/lightx2v_T2V_14B_cfg_step_distill_v2_lora_rank64_bf16.safetensors)
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Download [Wan-Alpha VAE] ()
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Download [Wan-Alpha T2V] ()
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## 🧪 Usage
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```bash
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bash test_lightx2v_dora.sh
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```
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**Prompt Writing Tip:** You need to specify that the background of the video is transparent, the visual style, the shot type (such as close-up, medium shot, wide shot, or extreme close-up), and a description of the main subject. Prompts support both Chinese and English input.
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```bash
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# An example of prompt.
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This video has a transparent background. Close-up shot. A colorful parrot flying. Realistic style.
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```
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## 🤝 Acknowledgements
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This project is built upon the following excellent open-source projects:
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* [DiffSynth-Studio](https://github.com/modelscope/DiffSynth-Studio) (training/inference framework)
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* [Wan2.1](https://github.com/Wan-Video/Wan2.1) (base video generation model)
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* [LightX2V](https://github.com/ModelTC/LightX2V) (inference acceleration)
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* [WanVideo_comfy](https://huggingface.co/Kijai/WanVideo_comfy) (inference acceleration)
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We sincerely thank the authors and contributors of these projects.
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---
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## ✏ Citation
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If you find our work helpful for your research, please consider citing our paper:
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```bibtex
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@article{
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}
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```
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---
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## 📬 Contact Us
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If you have any questions or suggestions, feel free to reach out via [GitHub Issues](https://github.com/WeChatCV/Wan-Alpha/issues) . We look forward to your feedback!
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