Instructions to use Dexmal/DM05-MEM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Dexmal/DM05-MEM with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForSeq2SeqLM model = AutoModelForSeq2SeqLM.from_pretrained("Dexmal/DM05-MEM", device_map="auto") - Notebooks
- Google Colab
- Kaggle
|
Download README.md from Dexmal/DM05-MEM: direct link, hf CLI and curl.
- Browser
- Download file 2.85 kB
-
https://huggingface.co/Dexmal/DM05-MEM/resolve/main/README.md
- Command line
-
hf download hf://Dexmal/DM05-MEM/README.md
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curl -L -o README.md https://huggingface.co/Dexmal/DM05-MEM/resolve/main/README.md
2.85 kB
| license: gemma | |
| library_name: transformers | |
| base_model: | |
| - Dexmal/DM05 | |
| tags: | |
| - robotics | |
| - vision-language-action | |
| - dm05 | |
| - opendm | |
| # DM05-mem | |
|  | |
| <p align="center"> | |
| <a href="https://www.dexmal.com/blog/dm0.5/index_en.html"><img src="https://img.shields.io/badge/π-Tech_Blog-blue" alt="Tech Blog"></a> | |
| <a href="https://github.com/dexmal/opendm"><img src="https://img.shields.io/badge/GitHub-OpenDM-181717?logo=github" alt="GitHub"></a> | |
| <a href="https://huggingface.co/Dexmal/DM05-MEM"><img src="https://img.shields.io/badge/Model-DM05--MEM-0EA5E9?logo=huggingface" alt="DM05-MEM"></a> | |
| <a href="https://maas.dexmal.com/"><img src="https://img.shields.io/badge/MaaS-Online-brightgreen.svg" alt="MaaS"></a> | |
| </p> | |
| OpenDM-format BF16 checkpoint for **DM05-mem** (32-slot history EEF). | |
| Use with [OpenDM](https://github.com/dexmal/opendm) `playground/dm05_mem.py`. | |
| See the [DM05 Inference Guide](https://github.com/dexmal/opendm/blob/main/docs/en/dm05_inference.md). | |
| Weights: BF16 `model.safetensors`. | |
| ## Model Card | |
| | Field | Value | | |
| | --- | --- | | |
| | Config | `playground/dm05_mem.py` | | |
| | Env vars | `DM05_MEM_CHECKPOINT` | | |
| | OpenDM `robot_type` | `ARX5` (playground default) | | |
| | Control | EEF (`control_mode=eef`) | | |
| | Cameras | Head / Left wrist / Right wrist | | |
| | Native state / action | 7 / 7 (xyz+rpy in, xyz+axis-angle+gripper out) | | |
| | Defaults | `action_horizon=50`, `is_history=true`, `speed=0.1`, `model_max_length=2048` | | |
| ## Use with OpenDM Inference | |
| ```bash | |
| # From the OpenDM repository root. | |
| hf download Dexmal/DM05-MEM \ | |
| --local-dir ./checkpoints/DM05-MEM | |
| pip install -e ".[fast-infer]" | |
| script/dm05_launcher.sh \ | |
| --exp playground/dm05_mem.py \ | |
| --task inference \ | |
| --model-config.model-name-or-path ./checkpoints/DM05-MEM \ | |
| --inference-config.port 7891 | |
| ``` | |
| Override with the env var used by the playground: | |
| ```bash | |
| export DM05_MEM_CHECKPOINT=/path/to/DM05-MEM | |
| python playground/dm05_mem.py | |
| python playground/dm05_mem.py --inference-config.backend fast | |
| ``` | |
| ## Runtime Profile | |
| From `playground/dm05_mem.py`: | |
| - `control_mode=eef`, `action_mode=absolute`, `speed=0.1` | |
| - `is_history=true`, `max_history_images=32` | |
| - attn: llm/action `sdpa`, vision `flash_attention_2` | |
| - fast: prefix `2048` | |
| ## Files | |
| ```text | |
| . | |
| βββ config.json | |
| βββ model.safetensors | |
| βββ norm_stats.json | |
| βββ tokenizer.json | |
| βββ tokenizer_config.json | |
| βββ processor_config.json | |
| βββ chat_template.jinja | |
| βββ generation_config.json | |
| βββ README.md | |
| ``` | |
| ## 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} | |
| } | |
| ``` | |