Instructions to use Efficient-Large-Model/Long-WAM-LIBERO-IDM-LeRobot with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- LeRobot
How to use Efficient-Large-Model/Long-WAM-LIBERO-IDM-LeRobot with LeRobot:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
Download policy_preprocessor_step_2_normalizer_processor.safetensors from Efficient-Large-Model/Long-WAM-LIBERO-IDM-LeRobot: direct link, hf CLI and curl.
- Browser
- Download file 408 Bytes
-
https://huggingface.co/Efficient-Large-Model/Long-WAM-LIBERO-IDM-LeRobot/resolve/main/policy_preprocessor_step_2_normalizer_processor.safetensors
- Command line
-
hf download hf://Efficient-Large-Model/Long-WAM-LIBERO-IDM-LeRobot/policy_preprocessor_step_2_normalizer_processor.safetensors
-
curl -L -o policy_preprocessor_step_2_normalizer_processor.safetensors https://huggingface.co/Efficient-Large-Model/Long-WAM-LIBERO-IDM-LeRobot/resolve/main/policy_preprocessor_step_2_normalizer_processor.safetensors
408 Bytes
- Xet hash:
- 069d94320f9266d73ec5c3711940e46601e648563fe467aac11c4997b38f39cd
- Size of remote file:
- 408 Bytes
- SHA256:
- ea4600df61939265ce95b392639c094f5e1de87f10dc19b1a37026e07c23fb29
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