Libero Object 1

🚀 Model Card for Hume-Libero_Object

This is a Dual-System Visual-Language-Action model with System-2 thinking, trained on Libero-Object. It offers a new approach to robotics applications.

• Paper: https://arxiv.org/abs/2505.21432
• Homepage: https://hume-vla.github.io
• Codebase: 🧰 Hume: A Dual-System VLA with System2 Thinking

🚀 Quick Start

✨ Features

This is a Dual-System Visual-Language-Action model with System-2 thinking trained on Libero-Object.

📦 Installation

No installation steps provided in the original document, so this section is skipped.

💻 Usage Examples

Basic Usage

from hume import HumePolicy
import numpy as np

# load policy
hume = HumePolicy.from_pretrained("/path/to/checkpoints")

# config Test-Time Computing args
hume.init_infer(
    infer_cfg=dict(
        replan_steps=8,
        s2_replan_steps=16,
        s2_candidates_num=5,
        noise_temp_lower_bound=1.0,
        noise_temp_upper_bound=1.0,
        time_temp_lower_bound=0.9,
        time_temp_upper_bound=1.0,
        post_process_action=True,
        device="cuda",
    )
)

# prepare observations
observation = {
    "observation.images.image": np.zeros((1,224,224,3), dtype = np.uint8), # (B, H, W, C)
    "observation.images.wrist_image": np.zeros((1,224,224,3), dtype = np.uint8), # (B, H, W, C)
    "observation.state": np.zeros((1, 7)), # (B, state_dim)
    "task": ["Lift the papper"],
}

# Infer the action
action = hume.infer(observation) # (B, action_dim)

📚 Documentation

• If you want to reproduce the results in paper, follow the instruction
• If you want to directly use the model, refer to the code example above.

🔧 Technical Details

No technical details provided in the original document, so this section is skipped.

📄 License

This project is licensed under the MIT license.

📋 Information Table

📖 Citation

@article{song2025hume,
  title={Hume: Introducing System-2 Thinking in Visual-Language-Action Model},
  author={Anonimous Authors},
  journal={arXiv preprint arXiv:2505.21432},
  year={2025}
}