Instructions to use openEuler/IB_Robot_ACT_dual_arm_banana_pick with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- LeRobot
How to use openEuler/IB_Robot_ACT_dual_arm_banana_pick with LeRobot:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
ACT banana pick โ dual arm (3 cameras)
Dual-arm ACT policy checkpoint for the banana-pick task with its Ascend OM compile and short verification clips. Legacy flat layout (no v3 inference manifest).
- Model type: ACT (Action Chunking Transformer)
- Source dataset:
dual_arm/yzh/yzh_0606
Observations / actions
| stream | shape |
|---|---|
observation.state |
12 (6 per arm) |
observation.images.top |
3ร240ร320 |
observation.images.left |
3ร240ร320 |
observation.images.right |
3ร240ร320 |
action |
12 |
Files
pytorch_model/โ PyTorch ACT weights (model.safetensors, ~2.3 GB), processor configs,train_config.json, and a Torch-side verification videoom_model/โ Ascend OM compile (model.om, ~923 MB) withconfig.om.json(schema v1,ascend_ombackend) and an OM-side verification video
Usage
Load the Torch checkpoint with LeRobot's ACT policy class. The OM artifact targets the Ascend (310P/310B) deployment of the same policy. For the current IB-Robot v3-bundle deployment path, see openEuler/IB_Robot_ACT_banana_pick_distill (single-arm distilled variant).