Improve model card: Add abstract and detailed quick start guide

This PR enhances the model card by:

1. **Adding the paper abstract**: Providing a concise overview of the model's purpose and key features directly on the model page.
2. **Including a detailed Quick Start guide**: Replacing the generic link to GitHub with the actual environment setup, model download instructions, and a runnable usage code snippet from the project's GitHub README. This makes it much easier for users to get started with the model directly from the Hugging Face Hub.

These changes aim to make the model card more comprehensive and user-friendly.

README.md

@@ -1,9 +1,10 @@
 ---
-license: apache-2.0
 base_model:
 - Wan-AI/Wan2.1-T2V-14B
+license: apache-2.0
 pipeline_tag: text-to-video
 ---
+
 <div align="center">
 
   <h1>
@@ -28,6 +29,12 @@ pipeline_tag: text-to-video
 
 ---
 
+## Abstract
+
+RGBA video generation, which includes an alpha channel to represent transparency, is gaining increasing attention across a wide range of applications. However, existing methods often neglect visual quality, limiting their practical usability. In this paper, we propose Wan-Alpha, a new framework that generates transparent videos by learning both RGB and alpha channels jointly. We design an effective variational autoencoder (VAE) that encodes the alpha channel into the RGB latent space. Then, to support the training of our diffusion transformer, we construct a high-quality and diverse RGBA video dataset. Compared with state-of-the-art methods, our model demonstrates superior performance in visual quality, motion realism, and transparency rendering. Notably, our model can generate a wide variety of semi-transparent objects, glowing effects, and fine-grained details such as hair strands. The released model is available on our website: this https URL .
+
+---
+
 ## 🔥 News
 * **[2025.09.30]** Released Wan-Alpha v1.0, the Wan2.1-14B-T2V–adapted weights and inference code are now open-sourced.
 
@@ -45,8 +52,88 @@ pipeline_tag: text-to-video
 
 ## 🚀 Quick Start
 
-Please see [Github](https://github.com/WeChatCV/Wan-Alpha) for code running details
+##### 1. Environment Setup
+```bash
+# Clone the project repository
+git clone https://github.com/WeChatCV/Wan-Alpha.git
+cd Wan-Alpha
+
+# Create and activate Conda environment
+conda create -n Wan-Alpha python=3.11 -y
+conda activate Wan-Alpha
+
+# Install dependencies
+pip install -r requirements.txt
+```
+
+##### 2. Model Download
+Download [Wan2.1-T2V-14B](https://huggingface.co/Wan-AI/Wan2.1-T2V-14B)
+
+Download [Lightx2v-T2V-14B](https://huggingface.co/Kijai/WanVideo_comfy/blob/main/Lightx2v/lightx2v_T2V_14B_cfg_step_distill_v2_lora_rank64_bf16.safetensors)
+
+Download [Wan-Alpha VAE](https://huggingface.co/htdong/Wan-Alpha)
+
+### 🧪 Usage
+You can test our model through:
+```bash
+torchrun --nproc_per_node=8 --master_port=29501 generate_dora_lightx2v.py --size 832*480\
+         --ckpt_dir "path/to/your/Wan-2.1/Wan2.1-T2V-14B" \
+         --dit_fsdp --t5_fsdp --ulysses_size 8 \
+         --vae_lora_checkpoint "path/to/your/decoder.bin" \
+         --lora_path "path/to/your/epoch-13-1500.safetensors" \
+         --lightx2v_path "path/to/your/lightx2v_T2V_14B_cfg_step_distill_v2_lora_rank64_bf16.safetensors" \
+         --sample_guide_scale 1.0 \
+         --frame_num 81 \
+         --sample_steps 4 \
+         --lora_ratio 1.0 \
+         --lora_prefix "" \
+         --prompt_file ./data/prompt.txt \
+         --output_dir ./output 
+```
+You can specify the weights of `Wan2.1-T2V-14B` with `--ckpt_dir`, `LightX2V-T2V-14B with` `--lightx2v_path`, `Wan-Alpha-VAE` with `--vae_lora_checkpoint`, and `Wan-Alpha-T2V` with `--lora_path`. Finally, you can find the rendered RGBA videos with a checkerboard background and PNG frames at `--output_dir`.
+
+**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.
+
+```bash
+# An example of prompt.
+This video has a transparent background. Close-up shot. A colorful parrot flying. Realistic style.
+```
+
+### 🔨 Official ComfyUI Version
+
+Note: We have reorganized our models to ensure they can be easily loaded into ComfyUI. Please note that these models differ from the ones mentioned above.
+
+1. Download models
+- The Wan DiT base model: [wan2.1_t2v_14B_fp16.safetensors](https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/blob/main/split_files/diffusion_models/wan2.1_t2v_14B_fp16.safetensors)
+- The Wan text encoder: [umt5_xxl_fp8_e4m3fn_scaled.safetensors](https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/blob/main/split_files/text_encoders/umt5_xxl_fp8_e4m3fn_scaled.safetensors)
+- The LightX2V model: [lightx2v_T2V_14B_cfg_step_distill_v2_lora_rank64_bf16.safetensors](https://huggingface.co/Kijai/WanVideo_comfy/blob/main/Lightx2v/lightx2v_T2V_14B_cfg_step_distill_v2_lora_rank64_bf16.safetensors)
+- Our RGBA Dora: [epoch-13-1500_changed.safetensors](https://huggingface.co/htdong/Wan-Alpha_ComfyUI/blob/main/epoch-13-1500_changed.safetensors)
+- Our RGB VAE Decoder: [wan_alpha_2.1_vae_rgb_channel.safetensors.safetensors](https://huggingface.co/htdong/Wan-Alpha_ComfyUI/blob/main/wan_alpha_2.1_vae_rgb_channel.safetensors.safetensors)
+- Our Alpha VAE Decoder: [wan_alpha_2.1_vae_alpha_channel.safetensors.safetensors](https://huggingface.co/htdong/Wan-Alpha_ComfyUI/blob/main/wan_alpha_2.1_vae_alpha_channel.safetensors.safetensors)
+
+2. Copy the files into the `ComfyUI/models` folder and organize them as follows:
+
+```
+ComfyUI/models
+├── diffusion_models
+��   └── wan2.1_t2v_14B_fp16.safetensors
+├── loras
+│   ├── epoch-13-1500_changed.safetensors
+│   └── lightx2v_T2V_14B_cfg_step_distill_v2_lora_rank64_bf16.safetensors
+├── text_encoders
+│   └── umt5_xxl_fp8_e4m3fn_scaled.safetensors
+├── vae
+│   ├── wan_alpha_2.1_vae_alpha_channel.safetensors.safetensors
+│   └── wan_alpha_2.1_vae_rgb_channel.safetensors.safetensors
+```
+
+3. Install our custom RGBA video previewer and PNG frames zip packer. Copy the file [RGBA_save_tools.py](comfyui/RGBA_save_tools.py) into the `ComfyUI/custom_nodes` folder.
+
+- Thanks to @mr-lab for an improved WebP version! You can find it in this [issue](https://github.com/WeChatCV/Wan-Alpha/issues/4).
+
+4. Example workflow: [wan_alpha_t2v_14B.json](comfyui/wan_alpha_t2v_14B.json)
 
+<img src="comfyui/comfyui.jpg" style="margin:auto;"/>
 
 
 ## 🤝 Acknowledgements
@@ -81,4 +168,4 @@ If you find our work helpful for your research, please consider citing our paper
 
 ## 📬 Contact Us
 
-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!
+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!