Instructions to use TInkybala/Real_Panda_Merged with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- LeRobot
How to use TInkybala/Real_Panda_Merged 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=TInkybala/Real_Panda_Merged \ --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=TInkybala/Real_Panda_Merged - Notebooks
- Google Colab
- Kaggle
Upload DataProcessorPipeline
Browse files
policy_postprocessor.json
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{
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"name": "policy_postprocessor",
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"steps": [
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{
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"registry_name": "unnormalizer_processor",
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"config": {
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"eps": 1e-08,
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"features": {
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"action": {
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"type": "ACTION",
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"shape": [
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7
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]
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}
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},
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"norm_map": {
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"VISUAL": "IDENTITY",
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"STATE": "MEAN_STD",
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"ACTION": "MEAN_STD"
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}
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},
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"state_file": "policy_postprocessor_step_0_unnormalizer_processor.safetensors"
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},
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{
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"registry_name": "device_processor",
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"config": {
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"device": "cpu",
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"float_dtype": null
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}
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}
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]
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}
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policy_postprocessor_step_0_unnormalizer_processor.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:557b4131870672191cf2cf80f7d55a6c87c32a50ecebf2bcb8d5bbb443f26d85
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size 6700
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