Robotics
Transformers
Safetensors
dm05
text-generation
robot-control
vision-language-action
vla
dm0.5
opendm
Instructions to use Dexmal/DM05 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Dexmal/DM05 with Transformers:
# Load model directly from transformers import AutoModelForSeq2SeqLM model = AutoModelForSeq2SeqLM.from_pretrained("Dexmal/DM05", dtype="auto") - Notebooks
- Google Colab
- Kaggle
| license: gemma | |
| library_name: transformers | |
| tags: | |
| - robotics | |
| - robot-control | |
| - vision-language-action | |
| - vla | |
| - dm05 | |
| - dm0.5 | |
| - opendm | |
| # DM05 | |
| [](https://github.com/dexmal/opendm) [](https://huggingface.co/Dexmal) [](https://www.dexmal.com/blog/dm0.5/index_en.html) | |
| DM05 is the base checkpoint of DM0.5, Dexmal's open-world | |
| Vision-Language-Action foundation model for embodied intelligence. It uses a | |
| Gemma3 4B vision-language backbone with a 680M Action Expert to generate | |
| continuous robot actions, and is designed for natural-language manipulation, | |
| zero-shot generalization, efficient downstream fine-tuning, long-horizon | |
| historical context, robust policy behavior, and transfer across robot | |
| embodiments. | |
| ## How to Use | |
| This model is intended to be used with OpenDM. See the | |
| [OpenDM README](https://github.com/dexmal/opendm) for installation, | |
| checkpoint download, inference, fine-tuning, and evaluation commands. | |
| ## Citation | |
| ```bibtex | |
| @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} | |
| } | |
| ``` | |