Jiafei1224/VLA-JEPA-MolmoAct2YAMData

VLA-JEPA MolmoAct2 BimanualYAM (3-cam, unfrozen Qwen)

Fine-tuned VLA-JEPA on the MolmoAct2-BimanualYAM-Dataset with 3 cameras (top, left, right) and an unfrozen Qwen3-VL-2B backbone.

Checkpoint details

Setting	Value
Training step	050000
Cameras	top, left, right
Action dim	14 (joint positions + grippers)
Chunk size	30 (@ 30 Hz)
Qwen	Qwen/Qwen3-VL-2B-Instruct (unfrozen)
Base model	lerobot/VLA-JEPA-Pretrain
Gripper range	[0, 1] (continuous, not binarized)

Usage (LeRobot)

from lerobot.policies.vla_jepa.modeling_vla_jepa import VLAJEPAPolicy

policy = VLAJEPAPolicy.from_pretrained("Jiafei1224/VLA-JEPA-MolmoAct2YAMData")

Usage (MolmoAct2 sim eval server)

See the MolmoAct2 sim_eval docs — serve via an /act HTTP endpoint with all three camera views.

Eval (step 050000)

• Open-loop: MSE 0.127, MAE 0.197 (50 held-out episodes)
• Closed-loop sim: 0% on BimanualYAMPutEverythingInBox-v1 (infra OK, task not solved yet)