Robotics
Transformers
Safetensors
English
rio2
feature-extraction
Mixture of Experts
diffusion-jepa
custom_code
Instructions to use hoguai/RIO-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hoguai/RIO-2 with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("hoguai/RIO-2", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
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- allenai/MolmoAct2-LIBERO-Dataset
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**RIO-2**
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RIO-2 is a two-rate WAM(World Action Model) built for robotics. RIO-2 is composed with a low-frequency visual-language S2 backbone and a high-frequency JEPA-diffusion S1 action policy. The model is designed to separate slow scene understanding from fast robot control:
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**RIO-2**
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RIO-2 is a two-rate WAM(World Action Model) built for robotics. RIO-2 is composed with a low-frequency visual-language S2 backbone and a high-frequency JEPA-diffusion S1 action policy. The model is designed to separate slow scene understanding from fast robot control:
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