Instructions to use jameslahm/yolov10n with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- YOLOv10
How to use jameslahm/yolov10n with YOLOv10:
from ultralytics import YOLOvv10 model = YOLOvv10.from_pretrained("jameslahm/yolov10n") source = 'http://images.cocodataset.org/val2017/000000039769.jpg' model.predict(source=source, save=True) - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cd3d5402b55c91e44dbeb731723fce533e4a9be944dc5a605136801595e0b67f
- Size of remote file:
- 11.2 MB
- SHA256:
- 98e5b4d81a20d1e8a972cd0be947944838ccd61f7f7e61828349a647d3607433
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