Instructions to use TRI-ML/multitask-dit-robosuite-wrist-diffusion-064000 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- LeRobot
How to use TRI-ML/multitask-dit-robosuite-wrist-diffusion-064000 with LeRobot:
- Notebooks
- Google Colab
- Kaggle
multitask-dit-robosuite-wrist-diffusion-064000
LeRobot Multi-task DiT policy trained on robosuite Lift, PickPlaceCan, and NutAssemblySquare with agentview and wrist camera inputs.
Source checkpoint: /home/anthonyliang/Documents/rfm_rl/outputs/multitask_dit_robosuite_wrist_diffusion_gpu0/checkpoints/064000/pretrained_model
Rollout Eval
Overall success rate: 0.9555555555555556 over 90 episodes.
| task | episodes | success_rate | avg_return | avg_steps |
|---|---|---|---|---|
| can | 30 | 1.0 | 26.727644266768134 | 105.33333333333333 |
| lift | 30 | 1.0 | 11.27891640541154 | 48.13333333333333 |
| square | 30 | 0.8666666666666667 | 45.49792050940882 | 189.7 |
Loading
Use this as a standard LeRobot pretrained policy checkpoint.
from lerobot.configs import PreTrainedConfig
from lerobot.policies import get_policy_class
cfg = PreTrainedConfig.from_pretrained("TRI-ML/multitask-dit-robosuite-wrist-diffusion-064000")
policy = get_policy_class(cfg.type).from_pretrained("{repo_id}", config=cfg)
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