A Vision-Language-Action (VLA) model fine-tuned on the SO100 Screw-Lid Dataset for robotic manipulation tasks.
This model is a SmolVLA variant trained specifically on the SO100 screw-lid manipulation task. It learns to perform the complete sequence: picking up a jar, placing it on a silicone puck, seating the lid with a half-turn, and transporting the assembled jar to a goal location.
The model was trained on 51 teleoperated demonstrations from the SO100 Screw-Lid Dataset, featuring:
1# Example usage with LeRobot
2from lerobot.common.policies import load_policy
3
4# Load the trained model
5policy = load_policy("Tomas0413/so100_screw_lid_smolvla")
6
7# Run inference on robot observations
8action = policy.select_action(observation)
This model was trained on the
SO100 Screw-Lid Dataset (v0), which contains 51 teleoperated episodes of the complete screw-lid manipulation sequence recorded during the LeRobot Worldwide Hackathon (June 15-16, 2025).