Robotics
Transformers
Safetensors
minicpm_robottrack
feature-extraction
vision-language-action
embodied-ai
minicpm
visual-tracking
custom_code
Instructions to use openbmb/MiniCPM-RobotTrack with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use openbmb/MiniCPM-RobotTrack with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("openbmb/MiniCPM-RobotTrack", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle

- Xet hash:
- 10cdac2ae8f084f60346459bac3bb4c070b5c600be1878b77a408a1f29ab635e
- Size of remote file:
- 85 kB
- SHA256:
- b7324cda4e3b05ada9a305bfffc72b1ebd92c9c255f8d6f475737f9e5b01c481
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.