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chomeed/mimicgen_square_d0_mtdit_flow_40k_robotstate9
mimicgen_square_d0_mtdit_flow_40k_robotstate9 is a robotics model from chomeed. Use it for the robotics task on the model card, and read the license before you ship it in a product. It is set up for lerobot.
LeRobot multitaskdit flow-matching policy for MimicGen SquareD0, trained for 40000 steps.
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From the Hugging Face model README
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:
observation.state = [ eef_pos(3) | eef_quat(4) | gripper_qpos(2) ] = 9
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).
| dataset | chomeed/mimicgen_square_d0_224x224, observation.state sliced to first 9 dims |
| policy | multi_task_dit, objective=flow_matching |
| steps | 40000 |
| batch size | 64 |
| seed | 1000 |
| optimizer | Adam, lr 2e-5, cosine schedule |
n_obs_steps | 2 |
n_action_steps | 24 |
horizon | 32 |
num_integration_steps | 100 (euler) |
| cameras | agentview, eye_in_hand (each 3×224×224) |
| action dim | 7 (OSC_POSE + gripper) |
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.