Step 7: Training — WALL-OSS Command
Reference Documentation
Install the Environment
Shell
cd lerobot
pip install -e ".[feetech,wallx]"Training Command Line
Shell
python lerobot/src/lerobot/scripts/lerobot_train.py \
--dataset.repo_id=Tommymy/lerobot_my_dataset_shake_hands \
--dataset.root=~/lerobot_my_dataset_shake_hands \
--policy.type=wall_x \
--output_dir=~/output_lerobot_train/shake/wallx_A \
--job_name=shake_wallx_a \
--policy.pretrained_name_or_path=x-square-robot/wall-oss-flow \
--policy.prediction_mode=diffusion \
--policy.attn_implementation=eager \
--policy.push_to_hub=false \
--wandb.enable=true \
--wandb.project=Lerobot_my_Project \
--steps=30000 \
--policy.device=cuda \
--batch_size=8The model archive is about 7.2G