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
File size: 2,852 Bytes
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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}
}
```
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