Model Card for pi05

Ο€β‚€.β‚… (Pi05) Policy

Ο€β‚€.β‚… is a Vision-Language-Action model with open-world generalization, from Physical Intelligence. The LeRobot implementation is adapted from their open source OpenPI repository.

Model Overview

Ο€β‚€.β‚… represents a significant evolution from Ο€β‚€, developed by Physical Intelligence to address a big challenge in robotics: open-world generalization. While robots can perform impressive tasks in controlled environments, Ο€β‚€.β‚… is designed to generalize to entirely new environments and situations that were never seen during training.

For more details, see the Physical Intelligence Ο€β‚€.β‚… blog post.

This policy has been trained and pushed to the Hub using LeRobot. See the full documentation at LeRobot Docs.


How to Get Started with the Model

For a complete walkthrough, see the training guide. Below is the short version on how to train and run inference/eval:

Train from scratch

lerobot-train \
  --dataset.repo_id=${HF_USER}/<dataset> \
  --policy.type=act \
  --output_dir=outputs/train/<desired_policy_repo_id> \
  --job_name=lerobot_training \
  --policy.device=cuda \
  --policy.repo_id=${HF_USER}/<desired_policy_repo_id>
  --wandb.enable=true

Writes checkpoints to outputs/train/<desired_policy_repo_id>/checkpoints/.

Evaluate the policy/run inference

lerobot-record \
  --robot.type=so100_follower \
  --dataset.repo_id=<hf_user>/eval_<dataset> \
  --policy.path=<hf_user>/<desired_policy_repo_id> \
  --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
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Dataset used to train pepijn223/pi05_libero_y