LeRobot multi_task_dit flow-matching policy for MimicGen Square_D0, trained for 40000 steps.

Unlike chomeed/mimicgen_three_piece_assembly_d0_flow_matching_prior_40k_robotstate9 (which keeps the full 51-D observation.state and slices to the first 9 inside the policy via n_state_dims), this model was trained on a dataset whose observation.state was pre-sliced to the first 9 dims:

i.e. the 42/14 privileged object dims were dropped from the data. config.json declares observation.state with shape [9], so this loads on stock LeRobot multi_task_dit (no n_state_dims field needed). The policy is vision-only for object state (agentview + eye_in_hand).

Evaluated on the Square_D0 robosuite env (headless OSMesa software rendering); success = env is_success reached at any step. Per-checkpoint success-rate curve: see square_d0_eval_success.png (added to this repo).

The CLIP text_model/vision_model ... UNEXPECTED warnings at load time are benign.