Upload README.md

README.md

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 ---
-license: apache-2.0
+language:
+- en
+pipeline_tag: image-to-video
+tags:
+- video-generation
+- image-to-video
+- world-model
+- robotics
+- action-conditioned
+- pytorch
+library_name: pytorch
+base_model:
+- Wan-AI/Wan2.2-TI2V-5B
 ---
+
+<div align="center">
+
+<h1>Boundless-World-Model</h1>
+
+<p align="center">
+  <strong>BWM: Physically consistent, action-conditioned video world model for robotic manipulation</strong>
+</p>
+
+<p align="center">
+  <a href="https://github.com/boundless-large-model/boundless-world-model"><img src="https://img.shields.io/badge/GitHub-Repository-blue?style=flat&logo=github" alt="GitHub Repository"></a>
+  <a href="https://huggingface.co/Wan-AI/Wan2.2-TI2V-5B"><img src="https://img.shields.io/badge/Base%20Model-Wan2.2--TI2V--5B-orange?style=flat&logo=huggingface" alt="Base Model"></a>
+  <a href="https://github.com/tsinghua-fib-lab/WorldArena"><img src="https://img.shields.io/badge/Benchmark-WorldArena-yellow?style=flat" alt="WorldArena"></a>
+</p>
+
+</div>
+
+## Model Details
+
+| Property | Value |
+|----------|-------|
+| **Base Model** | [Wan2.2-TI2V-5B](https://huggingface.co/Wan-AI/Wan2.2-TI2V-5B) |
+| **Resolution** | 480 x 640 |
+| **Frames** | 81 frames |
+| **Control Signals** | Robot action trajectories |
+| **Architecture** | Trainable DiT + Action Encoder |
+
+## Usage
+
+To use these weights, please refer to [our GitHub repository](https://github.com/boundless-large-model/boundless-world-model).
+
+## Acknowledgements
+
+This project builds upon the following open-source projects and benchmarks:
+
+- Wan2.2: https://github.com/Wan-Video/Wan2.2
+- DiffSynth-Studio: https://github.com/modelscope/DiffSynth-Studio
+- WorldArena: https://github.com/tsinghua-fib-lab/WorldArena/
+- ABot-PhysWorld: https://github.com/amap-cvlab/ABot-PhysWorld