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CoRL2026-CSI
/
SmolVLA-CaP-StackBlock-50epochs

Robotics
LeRobot
Safetensors
smolvla
vla
so101
code-as-policies
cap
imitation-learning
50epochs
single-arm
dual-camera
stack-block
rgb-blocks
blue-dish
Model card Files Files and versions
xet
Community

Instructions to use CoRL2026-CSI/SmolVLA-CaP-StackBlock-50epochs with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • LeRobot

    How to use CoRL2026-CSI/SmolVLA-CaP-StackBlock-50epochs 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=CoRL2026-CSI/SmolVLA-CaP-StackBlock-50epochs \
    --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=CoRL2026-CSI/SmolVLA-CaP-StackBlock-50epochs
  • Notebooks
  • Google Colab
  • Kaggle
SmolVLA-CaP-StackBlock-50epochs
907 MB
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  • 1 contributor
History: 2 commits
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  • .gitattributes
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  • README.md
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  • config.json
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  • model.safetensors
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  • policy_postprocessor.json
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  • policy_postprocessor_step_0_unnormalizer_processor.safetensors
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  • policy_preprocessor.json
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  • policy_preprocessor_step_5_normalizer_processor.safetensors
    16.8 kB
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  • train_config.json
    7.18 kB
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