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chore(rewards/robometer): default to lerobot/Robometer-4b model

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This commit is contained in:
Khalil Meftah
2026-05-21 14:15:31 +02:00
parent 1b559e1c84
commit a640d752bf
3 changed files with 7 additions and 7 deletions
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docs/source/robometer.mdx
+2 -2
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@@ -78,7 +78,7 @@ The model predicts per-frame progress and success internally. The LeRobot reward
from lerobot.rewards.robometer import RobometerConfig, RobometerRewardModel from lerobot.rewards.robometer import RobometerConfig, RobometerRewardModel
cfg = RobometerConfig( cfg = RobometerConfig(
pretrained_path="lilkm/Robometer-4B", pretrained_path="lerobot/Robometer-4B",
device="cuda", device="cuda",
reward_output="progress", reward_output="progress",
) )
@@ -119,7 +119,7 @@ from lerobot.rewards import make_reward_model, make_reward_model_config, make_re
cfg = make_reward_model_config( cfg = make_reward_model_config(
"robometer", "robometer",
pretrained_path="lilkm/Robometer-4B", pretrained_path="lerobot/Robometer-4B",
device="cuda", device="cuda",
image_key="observation.images.top", image_key="observation.images.top",
) )
src/lerobot/rewards/robometer/compute_rabc_weights.py
+4 -4
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@@ -33,13 +33,13 @@ Usage:
# Dense per-frame progress for one episode # Dense per-frame progress for one episode
python -m lerobot.rewards.robometer.compute_rabc_weights \\ python -m lerobot.rewards.robometer.compute_rabc_weights \\
--dataset-repo-id lerobot/libero_10_image \\ --dataset-repo-id lerobot/libero_10_image \\
--reward-model-path lilkm/Robometer-4B \\ --reward-model-path lerobot/Robometer-4B \\
--episodes 0 --episodes 0
# All episodes with batching # All episodes with batching
python -m lerobot.rewards.robometer.compute_rabc_weights \\ python -m lerobot.rewards.robometer.compute_rabc_weights \\
--dataset-repo-id lerobot/libero_10_image \\ --dataset-repo-id lerobot/libero_10_image \\
--reward-model-path lilkm/Robometer-4B \\ --reward-model-path lerobot/Robometer-4B \\
--batch-size 16 --batch-size 16
""" """
@@ -218,13 +218,13 @@ Examples:
# Dense per-frame progress for one episode # Dense per-frame progress for one episode
python -m lerobot.rewards.robometer.compute_rabc_weights \\ python -m lerobot.rewards.robometer.compute_rabc_weights \\
--dataset-repo-id lerobot/libero_10_image \\ --dataset-repo-id lerobot/libero_10_image \\
--reward-model-path lilkm/Robometer-4B \\ --reward-model-path lerobot/Robometer-4B \\
--episodes 0 --episodes 0
# All episodes, smaller batches for memory-constrained GPUs # All episodes, smaller batches for memory-constrained GPUs
python -m lerobot.rewards.robometer.compute_rabc_weights \\ python -m lerobot.rewards.robometer.compute_rabc_weights \\
--dataset-repo-id lerobot/libero_10_image \\ --dataset-repo-id lerobot/libero_10_image \\
--reward-model-path lilkm/Robometer-4B \\ --reward-model-path lerobot/Robometer-4B \\
--batch-size 16 --batch-size 16
""", """,
) )
src/lerobot/rewards/robometer/configuration_robometer.py
+1 -1
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@@ -50,7 +50,7 @@ ROBOMETER_SPECIAL_TOKENS = (
class RobometerConfig(RewardModelConfig): class RobometerConfig(RewardModelConfig):
"""Configuration for the Robometer reward model.""" """Configuration for the Robometer reward model."""
pretrained_path: str | None = "lilkm/Robometer-4B" pretrained_path: str | None = "lerobot/Robometer-4B"
image_key: str = OBS_IMAGES + ".top" image_key: str = OBS_IMAGES + ".top"
task_key: str = "task" task_key: str = "task"
default_task: str | None = None default_task: str | None = None