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params/: Orbax parameters for inference/evaluation.train_state/: full Orbax training state for resuming training.assets/: normalization statistics and checkpoint assets._CHECKPOINT_METADATA: Orbax checkpoint metadata.main. Assume that you download this checkpoint and put it in the directory checkpoints, to run the policy as server, please run:bash serve_policy.sh pi0_pretrain_vlabench_primitive_aligned checkpoints/pi0-pretrain-vlabench-primitive-aligned/bash multi_run_vlabench.sh <Your path to store the evaluate results>pi0_pretrain_vlabench_primitive_aligned.1XLA_PYTHON_CLIENT_MEM_FRACTION=0.95 uv run scripts/train.py pi0_pretrain_vlabench_primitive_aligned \
2 --exp-name=pi0_pretrain_vlabench_primitive_aligned \
3 --batch-size=32 \
4 --save_interval=10000 \
5 --overwrite1@article{zhang2024vlabench,
2 title={Vlabench: A large-scale benchmark for language-conditioned robotics manipulation with long-horizon reasoning tasks},
3 author={Zhang, Shiduo and Xu, Zhe and Liu, Peiju and Yu, Xiaopeng and Li, Yuan and Gao, Qinghui and Fei, Zhaoye and Yin, Zhangyue and Wu, Zuxuan and Jiang, Yu-Gang and others},
4 journal={arXiv preprint arXiv:2412.18194},
5 year={2024}
6}