Update README.md

README.md

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-license: apache-2.0
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+# HEX Model Checkpoint
+
+This repository hosts the pretrained checkpoint of [**HEX: Humanoid-Aligned Experts for Cross-Embodiment Whole-Body Manipulation**](https://arxiv.org/abs/2604.07993).
+
+**HEX** is a humanoid whole-body Vision-Language-Action model for cross-embodiment manipulation. The released checkpoint contains the pretrained model weights and configuration files required for model inference.
+
+
+## Repository Contents
+
+| Model | Params | Description |
+|:-----:|:------:|:------------|
+| HEX | 2.4B | Pretrained HEX checkpoint for humanoid whole-body manipulation |
+
+
+This repository contains the pretrained HEX checkpoint files, including model weights and the corresponding configuration files.
+
+
+## Download
+
+Please follow the instructions in the [HEX GitHub repository](https://github.com/Cognition2Action-Lab/HEX) to download and use the checkpoint.
+
+You may also download the checkpoint directly with the Hugging Face CLI:
+
+```bash
+huggingface-cli download Cognition2ActionLab/HEX-model \
+  --local-dir /path/to/save/HEX-model
+```
+
+Or with Python:
+
+```python
+from huggingface_hub import snapshot_download
+
+snapshot_download(
+    repo_id="Cognition2ActionLab/HEX-model",
+    repo_type="model",
+    local_dir="/path/to/save/HEX-model",
+)
+```
+
+## Base Model Requirement
+
+HEX uses [**Qwen3-VL**](https://huggingface.co/Qwen/Qwen3-VL-2B-Instruct) as the base vision-language model. Please download the Qwen3-VL model separately before running inference.
+
+
+
+## Dataset
+
+The processed HEX dataset is hosted in [Cognition2ActionLab/eai_real_world](https://huggingface.co/datasets/Cognition2ActionLab/eai_real_world).
+
+
+## License
+
+This checkpoint is released under the Apache-2.0 License.
+
+## Citation
+
+If you use this checkpoint, please cite our work:
+
+```bibtex
+@article{bai2026hex,
+  title={HEX: Humanoid-Aligned Experts for Cross-Embodiment Whole-Body Manipulation},
+  author={Bai, Shuanghao and Li, Meng and Lv, Xinyuan and Wang, Jiawei and Wang, Xinhua and Liao, Fei and Hou, Chengkai and Gu, Langzhe and Zhou, Wanqi and Wu, Kun and others},
+  journal={arXiv preprint arXiv:2604.07993},
+  year={2026}
+}
+```