Instructions to use lerobot/eo1-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- LeRobot
How to use lerobot/eo1-base with LeRobot:
- Notebooks
- Google Colab
- Kaggle
metadata
license: mit
library_name: lerobot
pipeline_tag: robotics
tags:
- lerobot
- eo1
- vision-language-action
base_model: IPEC-COMMUNITY/EO-1-3B
EO-1 base for LeRobot
This is a lossless key-layout conversion of
IPEC-COMMUNITY/EO-1-3B at revision
fe0a015d9349bdf886d898809213b3574eedf1f9 for LeRobot's native eo1 policy implementation.
The checkpoint preserves the released EO-1 Qwen vision-language weights, language-model head, state/action projectors, and flow-matching head. Its defaults match the release: action chunk size 16, maximum state/action dimension 32, two action-projector layers, and ten denoising steps.
Use --policy.path=lerobot/eo1-base for training or rollout. LeRobot then
applies the dataset or environment's camera, state, and action feature shapes
before instantiating the policy.