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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}
}
``` |