makepluscode/pick_red
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How to use makepluscode/ch10-01-smolvla-pick-red-60k with LeRobot:
# See https://github.com/huggingface/lerobot?tab=readme-ov-file#installation for more details git clone https://github.com/huggingface/lerobot.git cd lerobot pip install -e .[smolvla]
# Launch finetuning on your dataset python lerobot/scripts/train.py \ --policy.path=makepluscode/ch10-01-smolvla-pick-red-60k \ --dataset.repo_id=lerobot/svla_so101_pickplace \ --batch_size=64 \ --steps=20000 \ --output_dir=outputs/train/my_smolvla \ --job_name=my_smolvla_training \ --policy.device=cuda \ --wandb.enable=true
# Run the policy using the record function
python -m lerobot.record \
--robot.type=so101_follower \
--robot.port=/dev/ttyACM0 \ # <- Use your port
--robot.id=my_blue_follower_arm \ # <- Use your robot id
--robot.cameras="{ front: {type: opencv, index_or_path: 8, width: 640, height: 480, fps: 30}}" \ # <- Use your cameras
--dataset.single_task="Grasp a lego block and put it in the bin." \ # <- Use the same task description you used in your dataset recording
--dataset.repo_id=HF_USER/dataset_name \ # <- This will be the dataset name on HF Hub
--dataset.episode_time_s=50 \
--dataset.num_episodes=10 \
--policy.path=makepluscode/ch10-01-smolvla-pick-red-60kSmolVLA fine-tuned on makepluscode/pick_red for the SO-101 red-block pick task,
trained via LeLab for 60,000 steps (final loss ~0.084).
| Item | Value |
|---|---|
| Policy | SmolVLA |
| Base | lerobot/smolvla_base |
| Dataset | makepluscode/pick_red |
| Steps | 60,000 |
| Hardware | SO-101 leader/follower |
from lerobot.policies.smolvla.modeling_smolvla import SmolVLAPolicy
policy = SmolVLAPolicy.from_pretrained("makepluscode/ch10-01-smolvla-pick-red-60k")
Pre/post-processors (policy_preprocessor.json / policy_postprocessor.json)
in this repo are loaded together by from_pretrained.