How to use wjstx/pick_tube_05_tactile_decoder_deploy 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=wjstx/pick_tube_05_tactile_decoder_deploy \ --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=wjstx/pick_tube_05_tactile_decoder_deploy
https://huggingface.co/wjstx/pick_tube_05_tactile_decoder_deploy/resolve/main/tokenizer/processor_config.json
hf download hf://wjstx/pick_tube_05_tactile_decoder_deploy/tokenizer/processor_config.json
curl -L -o processor_config.json https://huggingface.co/wjstx/pick_tube_05_tactile_decoder_deploy/resolve/main/tokenizer/processor_config.json
