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-# Coming Soon...
+
WAM-Diff: A Masked Diffusion VLA Framework with MoE and Online Reinforcement Learning for Autonomous Driving
+
+
+
+
+ 1Fudan University 2Yinwang Intelligent Technology Co., Ltd
+
+
+## 🔧️ Framework
+
+
+## 📅️ Roadmap
+
+| Status | Milestone | ETA |
+| :----: | :----------------------------------------------------------------------------------------------------: | :--------: |
+| 🚀 | **[Releasing the inference source code](https://github.com/fudan-generative-vision/WAM-Diff)** | 2025.12.21 |
+| 🚀 | **[Pretrained models on Huggingface](https://huggingface.co/fudan-generative-ai/WAM-Diff)** | TBD |
+| 🚀 | **[Releasing the training scripts](#training)** | TBD |
+
+
+### Quick Inference Demo
+The [WAM-Diff](TBD) is now available on Hugging Face Hub. To quickly test the model, follow these simple steps:
+
+1. **Clone the repository**
+ ```bash
+ git clone https://github.com/fudan-generative-vision/WAM-Diff
+ cd WAM-Diff
+ ```
+2. **Initialize the environment**
+ Run the environment setup script to install necessary dependencies:
+ ```bash
+ bash init_env.sh
+ ```
+3. **Prepare the Model**
+ Download the pretrained WAM-Diff model from Hugging Face to the `./model/WAM-Diff` directory:
+ ```
+ https://huggingface.co/fudan-generative-ai/WAM-Diff
+ ```
+ Download the pretrained Siglip2 model from Hugging Face to the `./model/siglip2-so400m-patch14-384` directory:
+ ```
+ https://huggingface.co/google/siglip2-so400m-patch14-384
+ ```
+
+
+3. **Run the demo script**
+ Execute the demo script to test WAM-Diff on an example image:
+ ```bash
+ bash ./train/inf.sh
+ ```
+
+
+## 🤗 Acknowledgements
+We gratefully acknowledge the contributors to the [LLaDA-V](https://github.com/ML-GSAI/LLaDA-V), repositories, whose commitment to open source has provided us with their excellent codebases and pretrained models.
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