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Dexmal/DM05-Lerobot-LIBERO
DM05-Lerobot-LIBERO is a robotics model from Dexmal. 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 gemma.
DM05-Lerobot-LIBERO is a LIBERO-specific fine-tuned checkpoint based on Dexmal/DM05-Lerobot. It is not the general-purpose DM05 base model.
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From the Hugging Face model README
DM05-Lerobot-LIBERO is a LIBERO-specific fine-tuned checkpoint based on
Dexmal/DM05-Lerobot. It is not the general-purpose DM05 base model.
front, wrist87chunk_size=10n_action_steps=10add_state=falseuse_relative_actions=falseFor evaluation, use the LIBERO relative-controller protocol. The processor keeps the model action representation absolute; the controller protocol is an evaluation-time environment setting.
The reported 50k-step result covers 40 tasks x 5 episodes per task = 200 episodes:
| Suite | Successes |
|---|---|
| Spatial | 49/50 |
| Object | 50/50 |
| Goal | 50/50 |
| LIBERO-10 | 48/50 |
| Total | 197/200 = 98.5% |
This is a 200-episode evaluation result, not a standard 2,000-episode complete LIBERO evaluation score.
MUJOCO_GL=egl lerobot-eval \
--policy.path=Dexmal/DM05-Lerobot-LIBERO \
--env.type=libero \
--env.task=libero_spatial,libero_object,libero_goal,libero_10 \
--env.camera_name_mapping='{"agentview_image":"front","robot0_eye_in_hand_image":"wrist"}' \
--env.observation_height=256 \
--env.observation_width=256 \
--env.control_mode=relative \
--eval.n_episodes=5 \
--eval.batch_size=1 \
--seed=7 \
--policy.device=cuda
@misc{dm05,
title = {{DM0.5}: An Open-World Foundation Model for General-Purpose Embodied Intelligence},
author = {{Dexmal Team}},
month = {July},
year = {2026},
url = {https://www.dexmal.com/blog/dm0.5/index_en.html}
}