Instructions to use tonghuiwang123/so100-pi05-new60-ft with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- LeRobot
How to use tonghuiwang123/so100-pi05-new60-ft with LeRobot:
- Notebooks
- Google Colab
- Kaggle
so100-pi05-new60-ft · step 76000
Pi0.5 policy for SO-ARM100 / SO100 — Grab the white cube to the white cup
- 数据:
tonghuiwang123/4060 episodes / 13454 frames / 2×1280x720 @30fps - Checkpoint: step 76000 ≈ 45.2 epoch(有效 batch 8 = 4×2 DDP)
- 起点: 旧60集(旧相机)训练的 pi0560 权重(两阶段)
- 配置:
dtype=bfloat16,train_expert_only=true,gradient_checkpointing=true - 可训练参数 693M / 总 4.14B(VLM 冻结)
相机命名(Pi0.5 专用,与 ACT/SmolVLA 不同)
| 物理位置 | 设备 | 本模型要求的 key |
|---|---|---|
| 顶部 (top-down) | /dev/video2 |
base_0_rgb |
| 腕部 (wrist) | /dev/video4 |
left_wrist_0_rgb |
部署
lerobot-record \
--robot.type=so100_follower --robot.port=/dev/ttyACM0 \
--robot.id=my_awesome_follower_arm \
--robot.cameras="{
base_0_rgb: {type: opencv, index_or_path: /dev/video2, width: 1280, height: 720, fps: 30},
left_wrist_0_rgb: {type: opencv, index_or_path: /dev/video4, width: 1280, height: 720, fps: 30},
}" \
--dataset.repo_id=tonghuiwang123/eval_so100-pi05-new60-ft \
--dataset.single_task="Grab the white cube to the white cup" \
--policy.path=tonghuiwang123/so100-pi05-new60-ft
分辨率必须 1280x720。推理显存约 9.9 GB,需 12G 以上显卡。
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