Robotics
Transformers
Safetensors
minicpm_robottrack
feature-extraction
vision-language-action
embodied-ai
minicpm
visual-tracking
custom_code
Instructions to use dzfgfdhzsfhdfh/MiniCPM-RobotTrack with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dzfgfdhzsfhdfh/MiniCPM-RobotTrack with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("dzfgfdhzsfhdfh/MiniCPM-RobotTrack", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.model from dzfgfdhzsfhdfh/MiniCPM-RobotTrack: direct link, hf CLI and curl.
- Browser
- Download file 1.18 MB
-
https://huggingface.co/dzfgfdhzsfhdfh/MiniCPM-RobotTrack/resolve/main/tokenizer.model
- Command line
-
hf download hf://dzfgfdhzsfhdfh/MiniCPM-RobotTrack/tokenizer.model
-
curl -L -o tokenizer.model https://huggingface.co/dzfgfdhzsfhdfh/MiniCPM-RobotTrack/resolve/main/tokenizer.model
1.18 MB
- Xet hash:
- 7ed797a9c35425de87a74220399918ec298b96da3cc3cf869f8d740bbde29e59
- Size of remote file:
- 1.18 MB
- SHA256:
- bb74d51116831c3bf65db812c553f94ab0c88dcf97a5bbb37e3504f6d359c530
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