ShubhamK32/smolvla_so101_declutter

SmolVLA — SO-101 Space Decluttering

SmolVLA policy fine-tuned on the SO-101 Space Decluttering Dataset v1 for language-conditioned pick-and-place decluttering tasks on a 6-DoF SO-101 robotic arm. Trained using LeRobot.

Training Details

• Policy: SmolVLA (Vision-Language-Action)
• Steps: 20,000
• Robot: SO-101 6-DoF leader-follower
• Cameras: Dual-view — fixed top-view + wrist-mounted egocentric
• Framework: LeRobot
• Language conditioning: Task descriptions passed as natural language instructions

Dataset

Trained on ShubhamK32/so101_declutter_v1 — a multi-view teleoperation dataset with spatial distractors injected to prevent visual shortcut learning.

Usage

from lerobot.policies.smolvla.modeling_smolvla import SmolVLAPolicy

policy = SmolVLAPolicy.from_pretrained("ShubhamK32/smolvla_so101_declutter")

Camera Views

• observation.images.topview — Fixed overhead. Better for unoccluded pick-place tasks.
• observation.images.wristview — Egocentric wrist-mounted. Better for overlapping and cluttered scenes.

Related

• Dataset: ShubhamK32/so101_declutter_v1
• ACT checkpoint: ShubhamK32/act_so101_declutter