Instructions to use WetLabRoboData/diffusion-salt-scratch with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- LeRobot
How to use WetLabRoboData/diffusion-salt-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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Download README.md from WetLabRoboData/diffusion-salt-scratch: direct link, hf CLI and curl.
- Browser
- Download file 1.34 kB
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https://huggingface.co/WetLabRoboData/diffusion-salt-scratch/resolve/main/README.md
- Command line
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hf download hf://WetLabRoboData/diffusion-salt-scratch/README.md
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curl -L -o README.md https://huggingface.co/WetLabRoboData/diffusion-salt-scratch/resolve/main/README.md
1.34 kB
metadata
license: apache-2.0
library_name: lerobot
tags:
- lerobot
- diffusion-policy
- imitation-learning
- robotics
- ur3e
- bimanual
datasets:
- WetLabRoboData/lerobot-data-salt
pipeline_tag: robotics
diffusion-salt-scratch
LeRobot diffusion policy for the salt task.
| Field | Value |
|---|---|
| Policy family | diffusion (LeRobot) |
| Variant | Scratch (trained only on this task's data) |
| Training dataset | WetLabRoboData/lerobot-data-salt |
| Target task | salt | | Eval episodes | 20 | | Eval successes | 6 / 20 | | Robot | UR3e bimanual (3 cameras) |
Evaluation
Rollout videos + per-episode outcomes: WetLabRoboData/eval-diffusion-salt-scratch.
Load and deploy
from lerobot.policies.diffusion.modeling_diffusion import DiffusionPolicy
policy = DiffusionPolicy.from_pretrained("WetLabRoboData/diffusion-salt-scratch")
Provenance
Reorganized from WetLabRoboData/lerobot-data-smrithi-salt_20260725 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.