--- datasets: ases200q2/PandaPickCubeSpacemouseRandom2_v30 library_name: lerobot license: apache-2.0 model_name: pi0 pipeline_tag: robotics tags: - lerobot - robotics - pi0 --- # Model Card for pi0 **π₀ (Pi0)** π₀ is a Vision-Language-Action model for general robot control, from Physical Intelligence. The LeRobot implementation is adapted from their open source OpenPI repository. **Model Overview** π₀ represents a breakthrough in robotics as the first general-purpose robot foundation model developed by Physical Intelligence. Unlike traditional robots that are narrow specialists programmed for repetitive motions, π₀ is designed to be a generalist policy that can understand visual inputs, interpret natural language instructions, and control a variety of different robots across diverse tasks. For more details, see the [Physical Intelligence π₀ blog post](https://www.physicalintelligence.company/blog/pi0). This policy has been trained and pushed to the Hub using [LeRobot](https://github.com/huggingface/lerobot). See the full documentation at [LeRobot Docs](https://huggingface.co/docs/lerobot/index). --- ## How to Get Started with the Model For a complete walkthrough, see the [training guide](https://huggingface.co/docs/lerobot/il_robots#train-a-policy). Below is the short version on how to train and run inference/eval: ### Train from scratch ```bash lerobot-train \ --dataset.repo_id=${HF_USER}/ \ --policy.type=act \ --output_dir=outputs/train/ \ --job_name=lerobot_training \ --policy.device=cuda \ --policy.repo_id=${HF_USER}/ --wandb.enable=true ``` _Writes checkpoints to `outputs/train//checkpoints/`._ ### Evaluate the policy/run inference ```bash lerobot-record \ --robot.type=so100_follower \ --dataset.repo_id=/eval_ \ --policy.path=/ \ --episodes=10 ``` Prefix the dataset repo with **eval\_** and supply `--policy.path` pointing to a local or hub checkpoint. --- ## Model Details - **License:** apache-2.0