Instructions to use Vombit/yolov10x_cs2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- YOLOv10
How to use Vombit/yolov10x_cs2 with YOLOv10:
from ultralytics import YOLOvv10 model = YOLOvv10.from_pretrained("Vombit/yolov10x_cs2") source = 'http://images.cocodataset.org/val2017/000000039769.jpg' model.predict(source=source, save=True) - ultralytics
How to use Vombit/yolov10x_cs2 with ultralytics:
from ultralytics import YOLOvv10 model = YOLOvv10.from_pretrained("Vombit/yolov10x_cs2") source = 'http://images.cocodataset.org/val2017/000000039769.jpg' model.predict(source=source, save=True) - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 456d675f0bfea5d9673184ab72ad05ff5de10d3e59de4eb8af40709c49032ff7
- Size of remote file:
- 64.1 MB
- SHA256:
- bdcf894ebf3d5a872dac042c5c9b786bf0ae2139461b7716da9c5bfe13dcec16
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