--- license: apache-2.0 datasets: - Cognition2ActionLab/eai_real_world language: - en base_model: - Qwen/Qwen3-VL-2B-Instruct pipeline_tag: robotics tags: - VLA - Robotics - Humanoid --- # 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} } ```