leapshared/Redox_200epi_subtask_GR00T17

Model Card for groot_frozen_bf16

This is a groot_frozen_bf16 policy trained with LeRobot.

This policy has been trained and pushed to the Hub using LeRobot.

See the full LeRobot documentation.

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Model Details

• License: apache-2.0
• Robot type: bi_openarm_follower
• Cameras: follower_d455f, left_wrist, right_wrist

Inputs & Outputs

The policy consumes these observation features and produces these action features.

Inputs

Feature	Type	Shape
observation.state	STATE	(16,)
observation.images.follower_d455f	VISUAL	(3, 480, 640)
observation.images.left_wrist	VISUAL	(3, 480, 640)
observation.images.right_wrist	VISUAL	(3, 480, 640)

Outputs

Feature	Type	Shape
action	ACTION	(16,)

Training Dataset

• Repository: leapshared/Redox_200epi_subtask
• Episodes: 200
• Frames: 193755
• Frame rate: 30 FPS
• Task(s): "Hold the metal plate by the orange handle, dip it into the blue solution, take it out and point at it, then put the plate back in the beaker on the left.. lift the metal plate out of the left beaker", "Hold the metal plate by the orange handle, dip it into the blue solution, take it out and point at it, then put the plate back in the beaker on the left.. move the plate over the blue solution", "Hold the metal plate by the orange handle, dip it into the blue solution, take it out and point at it, then put the plate back in the beaker on the left.. point at the plate with the left hand", "Hold the metal plate by the orange handle, dip it into the blue solution, take it out and point at it, then put the plate back in the beaker on the left.. lower the plate into the blue solution", "Hold the metal plate by the orange handle, dip it into the blue solution, take it out and point at it, then put the plate back in the beaker on the left.. hold the plate still in the solution", "Hold the metal plate by the orange handle, dip it into the blue solution, take it out and point at it, then put the plate back in the beaker on the left.. raise the plate and point at it", "Hold the metal plate by the orange handle, dip it into the blue solution, take it out and point at it, then put the plate back in the beaker on the left.. put the plate into the left beaker", "Hold the metal plate by the orange handle, dip it into the blue solution, take it out and point at it, then put the plate back in the beaker on the left.. return to the home posture"

Training Configuration

Setting	Value
Training steps	40000
Batch size	16
Optimizer	adamw_fused
Learning rate	0.0001
Seed	42
LeRobot version	0.6.1

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How to Get Started with the Model

New to LeRobot? These guides cover the full workflow:

• Install LeRobot — set up the lerobot package.
• Hardware setup — assemble, wire, and calibrate your robot and cameras.
• Record data & train a policy — the end-to-end imitation-learning walkthrough.
• CLI cheat-sheet — quick reference for the lerobot-* commands.

The short version to run and train this policy:

Run the policy on your robot

lerobot-rollout \
  --strategy.type=base \
  --robot.type=bi_openarm_follower \
  --robot.port=<your_robot_port> \
  --robot.cameras="{ <camera_1>: {type: opencv, index_or_path: <index_or_path>, width: 640, height: 480, fps: 30}, <camera_2>: {type: opencv, index_or_path: <index_or_path>, width: 640, height: 480, fps: 30}}" \
  --policy.path=leapshared/Redox_200epi_subtask_GR00T17 \
  --task="Hold the metal plate by the orange handle, dip it into the blue solution, take it out and point at it, then put the plate back in the beaker on the left.. lift the metal plate out of the left beaker" \
  --duration=60

Replace the remaining <...> placeholders with your own values: --robot.port and the camera names/indices are specific to your machine, and the camera names must match the observation keys this policy was trained on.

When --strategy.type=base is used the script doesn't record the episodes. Skipping duration will make the policy run indefinitely. For more information look at rollout documentation.

Train your own policy

lerobot-train \
  --dataset.repo_id=${HF_USER}/<dataset> \
  --policy.type=groot_frozen_bf16 \
  --output_dir=outputs/train/<policy_repo_id> \
  --job_name=lerobot_training \
  --policy.device=cuda \
  --policy.repo_id=${HF_USER}/<policy_repo_id> \
  --wandb.enable=true

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

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Evaluation

No evaluation results have been provided for this policy yet.

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Citation

If you use this policy, please cite the method linked in the description above, along with LeRobot:

@misc{cadene2024lerobot,
    author = {Cadene, Remi and Alibert, Simon and Soare, Alexander and Gallouedec, Quentin and Zouitine, Adil and Palma, Steven and Kooijmans, Pepijn and Aractingi, Michel and Shukor, Mustafa and Aubakirova, Dana and Russi, Martino and Capuano, Francesco and Pascal, Caroline and Choghari, Jade and Moss, Jess and Wolf, Thomas},
    title = {LeRobot: State-of-the-art Machine Learning for Real-World Robotics in Pytorch},
    howpublished = "\url{https://github.com/huggingface/lerobot}",
    year = {2024}
}