metadata
license: apache-2.0
library_name: lerobot
tags:
- lerobot
- diffusion-policy
- imitation-learning
- robotics
- ur3e
- bimanual
datasets:
- WetLabRoboData/lerobot-data-uncap
pipeline_tag: robotics
diffusion-uncap-scratch
LeRobot diffusion policy for the uncap task.
| Field | Value |
|---|---|
| Policy family | diffusion (LeRobot) |
| Variant | Scratch (trained only on this task's data) |
| Training dataset | WetLabRoboData/lerobot-data-uncap |
| Target task | uncap | | Eval episodes | 20 | | Eval successes | 19 / 20 | | Robot | UR3e bimanual (3 cameras) |
Evaluation
Rollout videos + per-episode outcomes: WetLabRoboData/eval-diffusion-uncap-scratch.
Load and deploy
from lerobot.policies.diffusion.modeling_diffusion import DiffusionPolicy
policy = DiffusionPolicy.from_pretrained("WetLabRoboData/diffusion-uncap-scratch")
Provenance
Reorganized from WetLabRoboData/lerobot-data-smrithi-uncap_20260713 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.