Instructions to use Vombit/yolov10n_cs2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- YOLOv10
How to use Vombit/yolov10n_cs2 with YOLOv10:
from ultralytics import YOLOvv10 model = YOLOvv10.from_pretrained("Vombit/yolov10n_cs2") source = 'http://images.cocodataset.org/val2017/000000039769.jpg' model.predict(source=source, save=True) - ultralytics
How to use Vombit/yolov10n_cs2 with ultralytics:
from ultralytics import YOLOvv10 model = YOLOvv10.from_pretrained("Vombit/yolov10n_cs2") source = 'http://images.cocodataset.org/val2017/000000039769.jpg' model.predict(source=source, save=True) - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cd69e1499489f30597ab9c287bd832ab7e52309f0a82e90dad1825f773de6442
- Size of remote file:
- 5.77 MB
- SHA256:
- e56cc66ccbb21c40bd56390f9a9d5a9719f9ba7e9729e091feac982c6e9bae8e
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