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BrianZhengJourney/
sarm_libero_bowl

Name: sarm_libero_bowl
Availability: InStock

BrianZhengJourney/libero_bowl_sarm

apache-2.0

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Reward Model Card for sarm

A Success-Aware Reward Model (SARM) predicts a dense reward signal from observations, typically used downstream for reinforcement learning or human-in-the-loop fine-tuning when task success is not directly observable.

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

How to Get Started with the Reward Model

Train from scratch

bash

lerobot-train \
  --dataset.repo_id=${HF_USER}/<dataset> \
  --reward_model.type=sarm \
  --output_dir=outputs/train/<desired_reward_model_repo_id> \
  --job_name=lerobot_reward_training \
  --reward_model.device=cuda \
  --reward_model.repo_id=${HF_USER}/<desired_reward_model_repo_id> \
  --wandb.enable=true

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

Load the reward model in Python

python

from lerobot.rewards import make_reward_model

reward_model = make_reward_model(pretrained_path="<hf_user>/<reward_model_repo_id>")
reward = reward_model.compute_reward(batch)

Model Details

License: apache-2.0

BrianZhengJourney/sarm_libero_bowl