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mtdit_croissant_jointbase_h48
maskjp/mtdit_croissant_jointbase_h48
mtdit_croissant_jointbase_h48 is a robotics model from maskjp. 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. The card lists the license as apache-2.0.
Multi-Task DiT policy trained with LeRobot on l5vel-peng/base4-plate-croissant-eef-merged-v30 (98 episodes, ~155k frames, 50 fps).
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At a glance
- Task
- Robotics
- Library
- lerobot
- License
- apache-2.0
- Access
- Public
- Created
- Aug 25, 2026
- Updated
- Aug 25, 2026
- SHA
- 55236a6c
Model card
From the Hugging Face model README
mtdit_croissant_jointbase_h48
Multi-Task DiT policy trained with LeRobot on
l5vel-peng/base4-plate-croissant-eef-merged-v30 (98 episodes, ~155k frames, 50 fps).
Final checkpoint: step 100,000 (train loss 0.001, held-out eval loss 0.0141).
Action space
Joint + base, 10-D — [joint1..joint6, gripper, base_x, base_y, base_yaw] under the keys
observation.state / action. The dataset also carries 13-D EEF variants
(observation.eef_state / action.eef); those columns ride along in the metadata but are
not fed to the model, since LeRobot keys the policy off the exact names
observation.state and action.
Observations: three 480×640 RGB cameras (left, right, wrist), randomly cropped to 224×224.
Configuration
| objective | diffusion (DDPM, 100 train timesteps) |
| horizon | 48 (0.96 s @ 50 Hz) |
| n_action_steps | 32 (0.64 s executed per call) |
| n_obs_steps | 2 |
| hidden_dim / layers / heads | 512 / 6 / 8 |
| vision + text encoder | openai/clip-vit-base-patch16 |
| optimizer lr | 1e-4, 2000 warmup steps |
| batch size | 32 per GPU × 7 GPUs (DDP) = 224 effective |
| steps | 100,000 (~151 epochs) |
| precision | bf16 |
| seed | 1000 |
| eval split | 0.05 (~5 held-out episodes) |
Usage
from lerobot.policies.multi_task_dit.modeling_multi_task_dit import MultiTaskDiTPolicy
policy = MultiTaskDiTPolicy.from_pretrained("maskjp/mtdit_croissant_jointbase_h48")
Training
Reproduced with train_mtdit_croissant.sh in the training repo:
torchrun --nproc_per_node=7 -m lerobot.scripts.lerobot_train \
--dataset.repo_id=l5vel-peng/base4-plate-croissant-eef-merged-v30 \
--dataset.eval_split=0.05 \
--policy.type=multi_task_dit --policy.objective=diffusion \
--policy.horizon=48 --policy.n_action_steps=32 --policy.n_obs_steps=2 \
--policy.optimizer_lr=1e-4 --policy.scheduler_warmup_steps=2000 \
--batch_size=32 --steps=100000 --accelerator.mixed_precision=bf16 --seed=1000
- Task
- Robotics
- Library
- lerobot
- License
- apache-2.0
- Created
- Aug 25, 2026
- Updated
- Aug 25, 2026