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danielsanjosepro/ditmeanflow_drawer_v2_lognorm

sourceHugging Faceapache-2.0updated 10mo agoView on Hugging Face
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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

bash
python -m lerobot.scripts.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/<desiredpolicyrepoid>/checkpoints/`._

Evaluate the policy/run inference

bash
python -m 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