villekuosmanen / armnetbench_open_lamp_door_diffusion

huggingface.co
Total runs: 10
24-hour runs: 0
7-day runs: 0
30-day runs: 5
Model's Last Updated: June 24 2026
robotics

Introduction of armnetbench_open_lamp_door_diffusion

Model Details of armnetbench_open_lamp_door_diffusion

Model Card for diffusion

Diffusion Policy treats visuomotor control as a generative diffusion process, producing smooth, multi-step action trajectories that excel at contact-rich manipulation.

This policy has been trained and pushed to the Hub using LeRobot . See the full documentation at LeRobot Docs .


How to Get Started with the Model

For a complete walkthrough, see the training guide . Below is the short version on how to train and run inference/eval:

Train from scratch
lerobot-train \
  --dataset.repo_id=${HF_USER}/<dataset> \
  --policy.type=act \
  --output_dir=outputs/train/<desired_policy_repo_id> \
  --job_name=lerobot_training \
  --policy.device=cuda \
  --policy.repo_id=${HF_USER}/<desired_policy_repo_id>
  --wandb.enable=true

Writes checkpoints to outputs/train/<desired_policy_repo_id>/checkpoints/ .

Evaluate the policy/run inference
lerobot-record \
  --robot.type=so100_follower \
  --dataset.repo_id=<hf_user>/eval_<dataset> \
  --policy.path=<hf_user>/<desired_policy_repo_id> \
  --episodes=10

Prefix the dataset repo with eval_ and supply --policy.path pointing to a local or hub checkpoint.


Model Details
  • License: apache-2.0

Runs of villekuosmanen armnetbench_open_lamp_door_diffusion on huggingface.co

10
Total runs
0
24-hour runs
1
3-day runs
0
7-day runs
5
30-day runs

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armnetbench_open_lamp_door_diffusion install

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