Instructions to use WetLabRoboData/diffusion-bimanual_pick-scratch with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- LeRobot
How to use WetLabRoboData/diffusion-bimanual_pick-scratch 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
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license: apache-2.0
library_name: lerobot
tags:
- lerobot
- diffusion-policy
- imitation-learning
- robotics
- ur3e
- bimanual
datasets:
- WetLabRoboData/lerobot-data-bimanual_pick
pipeline_tag: robotics
---
# diffusion-bimanual_pick-scratch
LeRobot diffusion policy for the **bimanual_pick** task.
| Field | Value |
|--------------------|-------|
| Policy family | diffusion (LeRobot) |
| Variant | Scratch (trained only on this task's data) |
| Training dataset | [`WetLabRoboData/lerobot-data-bimanual_pick`](https://huggingface.co/datasets/WetLabRoboData/lerobot-data-bimanual_pick) |
| Target task | bimanual_pick |
| Eval episodes | 20 |
| Eval successes | 16 / 20 |
| Robot | UR3e bimanual (3 cameras) |
## Evaluation
Rollout videos + per-episode outcomes: [`WetLabRoboData/eval-diffusion-bimanual_pick-scratch`](https://huggingface.co/datasets/WetLabRoboData/eval-diffusion-bimanual_pick-scratch).
## Load and deploy
```python
from lerobot.policies.diffusion.modeling_diffusion import DiffusionPolicy
policy = DiffusionPolicy.from_pretrained("WetLabRoboData/diffusion-bimanual_pick-scratch")
```
## Provenance
Reorganized from `WetLabRoboData/lerobot-data-bimanual_pick_20260624` on 2026-10-04. The archived
training outputs (checkpoints, train_config.json, wandb/) are preserved in
the `old/` subfolder of that source repo for traceability.
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