Robotics
Transformers
Safetensors
dm05
text-generation
vision-language-action
opendm
robochallenge
aloha
Instructions to use Dexmal/DM05-Table30v2-ALOHA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Dexmal/DM05-Table30v2-ALOHA with Transformers:
# Load model directly from transformers import AutoModelForSeq2SeqLM model = AutoModelForSeq2SeqLM.from_pretrained("Dexmal/DM05-Table30v2-ALOHA", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| license: gemma | |
| library_name: transformers | |
| base_model: | |
| - Dexmal/DM05 | |
| tags: | |
| - robotics | |
| - vision-language-action | |
| - dm05 | |
| - opendm | |
| - robochallenge | |
| - aloha | |
| # DM05-ALOHA(RoboChallenge) | |
| 面向 RoboChallenge Table 30 v2 **ALOHA** 机型的 OpenDM 格式 BF16 权重。 | |
| 请配合 [Dexbotic-RoboChallengeInference](https://github.com/dexmal) | |
| (`configs/generalist/aloha.yaml`)使用。 | |
| 权重文件为 BF16 `model.safetensors`。 | |
| ## 模型信息 | |
| | 字段 | 值 | | |
| | --- | --- | | |
| | 配置名 | `generalist/aloha` | | |
| | 环境变量 | `ALOHA_CHECKPOINT` / `ALOHA_NORM_STATS` | | |
| | OpenDM `robot_type` | `Aloha` | | |
| | 控制方式 | Joint 相对动作 | | |
| | 相机顺序 | Head / Left wrist / Right wrist | | |
| | 平台相机映射 | `cam_high` → image_0,`cam_left_wrist` → image_1,`cam_right_wrist` → image_2 | | |
| | 状态 / action 统计维度 | 14 / 14(`norm_stats.json` 仅含 action 分位数统计) | | |
| | 默认推理参数 | `action_horizon=25`,`is_history=false`,`inference_seed=0` | | |
| ## Table30 任务 | |
| `lint_roller_remove_dirt`、`pack_the_items`、`pack_the_toothbrush_holder`、`paint_jam`、 | |
| `put_the_books_back`、`put_the_pencil_case_into_the_schoolbag`、 | |
| `scoop_with_a_small_spoon`、`stamp_positioning`、`wipe_the_blackboard`、 | |
| `wrap_with_a_soft_cloth` | |
| 分任务 horizon 见 `configs/generalist/aloha.yaml` 的 `task_overrides` | |
| (例如 `put_the_books_back=15`、`stamp_positioning=45`、`wipe_the_blackboard=15`)。 | |
| ## 使用 Dexbotic-RoboChallengeInference | |
| ```bash | |
| cd /path/to/Dexbotic-RoboChallengeInference | |
| export OPENDM_ROOT=/path/to/opendm | |
| export ALOHA_CHECKPOINT=/path/to/DM05-ALOHA | |
| export ALOHA_NORM_STATS=$ALOHA_CHECKPOINT/norm_stats.json | |
| pip install -e "$OPENDM_ROOT" | |
| pip install -r requirements.txt | |
| python execute.py --config-name generalist/aloha \ | |
| user_id=YOUR_USER_ID \ | |
| submission_id=YOUR_SUBMISSION_ID | |
| ``` | |
| 不用环境变量时也可直接覆盖: | |
| ```bash | |
| python execute.py --config-name generalist/aloha \ | |
| checkpoint=/path/to/DM05-ALOHA \ | |
| norm_stats=/path/to/DM05-ALOHA/norm_stats.json \ | |
| user_id=YOUR_USER_ID \ | |
| submission_id=YOUR_SUBMISSION_ID | |
| ``` | |
| 若未设置 `ALOHA_NORM_STATS`,客户端会回退到 `$ALOHA_CHECKPOINT/norm_stats.json`。 | |
| ## 运行时配置 | |
| 来自 `configs/default.yaml` → `robot_profiles.aloha`: | |
| - `action_type=joint`,`action_mode=relative` | |
| - `is_history=false`,`add_state=true`,`speed=0.5` | |
| - `inference_seed=0`,`resize_name=padding` | |
| ## 目录结构 | |
| ```text | |
| . | |
| ├── config.json | |
| ├── model.safetensors | |
| ├── norm_stats.json | |
| ├── tokenizer.json | |
| ├── tokenizer_config.json | |
| ├── processor_config.json | |
| ├── chat_template.jinja | |
| ├── generation_config.json | |
| ├── README.md | |
| └── README_zh.md | |
| ``` | |
| ## 引用 | |
| ```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} | |
| } | |
| ``` | |