init

.gitattributes

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README.md

@@ -1,3 +1,73 @@
 ---
-license: bsd-3-clause
+license: apache-2.0
+language:
+- en
+pipeline_tag: image-text-to-text
+tags:
+- multimodal
+library_name: transformers
+base_model:
+- Qwen/Qwen2-VL-2B
 ---
+
+# G2VLM-2B-MoT
+## Geometry Grounded Vision Language Model with Unified 3D Reconstruction and Spatial Reasoning
+
+<p align="left">
+  <img src="https://huggingface.co/InternRobotics/G2VLM-2B-MoT/resolve/main/assets/icon.png" alt="G2VLM" width="200"/>
+</p>
+
+
+<p align="left">
+  <a href="https://gordonhu608.github.io/g2vlm.github.io/">
+    <img
+      src="https://img.shields.io/badge/G2VLM-Website-0A66C2?logo=safari&logoColor=white" style="display: inline-block; vertical-align: middle;"
+      alt="G2VLM Website"
+    />
+  </a>
+  <a href="https://arxiv.org/abs/2511.21688">
+    <img
+      src="https://img.shields.io/badge/G2VLM-Paper-red?logo=arxiv&logoColor=red" style="display: inline-block; vertical-align: middle;"
+      alt="G2VLM Paper on arXiv"
+    />
+  </a>
+  <a href="https://github.com/InternRobotics/G2VLM" target="_blank" style="margin: 2px;">
+      <img 
+        alt="Github" src="https://img.shields.io/badge/G2VLM-Codebase-536af5?color=536af5&logo=github" style="display: inline-block; vertical-align: middle;"
+        alt="G2VLM Codebase"
+      />
+  </a>
+</p>
+
+
+> We present <b>G<sup>2</sup>VLM</b>, a geometry grounded vision-language model proficient in both spatial 3D reconstruction and spatial understanding tasks. For spatial reasoning questions, G<sup>2</sup>VLM can natively predict 3D geometry and employ interleaved reasoning for an answer.
+
+
+This repository hosts the model weights for <b>G<sup>2</sup>VLM</b>. For installation, usage instructions, and further documentation, please visit our [GitHub repository](https://github.com/InternRobotics/G2VLM).
+
+
+<p align="left"><img src="https://huggingface.co/InternRobotics/G2VLM-2B-MoT/resolve/main/assets/teaser.png" width="100%"></p>
+
+
+
+## 🧠 Method
+<i>G<sup>2</sup>VLM is a unified model that integrates both a geometric perception expert for 3D reconstruction and a semantic perception expert for multimodal understanding and spatial reasoning tasks. All tokens can do shared multi-modal self attention in each transformer block.
+
+<p align="left"><img src="https://huggingface.co/InternRobotics/G2VLM-2B-MoT/resolve/main/assets/method.png" width="100%"></p>
+
+
+## License
+G2VLM is licensed under the Apache 2.0 license.
+
+## ✍️ Citation
+```bibtex
+@article{hu2025g2vlmgeometrygroundedvision,
+      title={G$^2$VLM: Geometry Grounded Vision Language Model with Unified 3D Reconstruction and Spatial Reasoning}, 
+      author={Wenbo Hu and Jingli Lin and Yilin Long and Yunlong Ran and Lihan Jiang and Yifan Wang and Chenming Zhu and Runsen Xu and Tai Wang and Jiangmiao Pang},
+      year={2025},
+      eprint={2511.21688},
+      archivePrefix={arXiv},
+      primaryClass={cs.CV},
+      url={https://arxiv.org/abs/2511.21688}, 
+}
+```

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