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Upload reward model weights, train config and readme
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metadata
datasets: lilkm/stackblocks_recap_all_for_vf
library_name: lerobot
license: apache-2.0
model_name: distributional_value_function
pipeline_tag: robotics
tags:
  - reward-model
  - robotics
  - distributional_value_function
  - lerobot

Reward Model Card for distributional_value_function

Reward model type not recognized — please update this template.

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

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

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