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kadiru/pi0fast_aiworker_bg2_pickplace_quest3_35demo_20k

sourceHugging Faceapache-2.0updated 3mo agoView on Hugging Face
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Model Card for pi0fast

<!-- Provide a quick summary of what the model is/does. -->

Pi0-Fast is a variant of Pi0 that uses a new tokenization method called FAST, which enables training of an autoregressive vision-language-action policy for high-frequency robotic tasks with improved performance and reduced training time.

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

bash
python -m lerobot.scripts.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/<desiredpolicyrepoid>/checkpoints/`._

Evaluate the policy/run inference

bash
python -m 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