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
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README.md
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- [yoloV10n_cs2](https://huggingface.co/Vombit/yolov10n_cs2) (5.5mb)
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- [yoloV10s_cs2](https://huggingface.co/Vombit/yolov10s_cs2) (15.7mb)
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- [yoloV10m_cs2](https://huggingface.co/Vombit/yolov10m_cs2) (31.9mb)
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## How to use
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```python
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- [yoloV10n_cs2](https://huggingface.co/Vombit/yolov10n_cs2) (5.5mb)
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- [yoloV10s_cs2](https://huggingface.co/Vombit/yolov10s_cs2) (15.7mb)
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- [yoloV10m_cs2](https://huggingface.co/Vombit/yolov10m_cs2) (31.9mb)
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- [yoloV10b_cs2](https://huggingface.co/Vombit/yolov10b_cs2) (39.7mb)
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- [yoloV10l_cs2](https://huggingface.co/Vombit/yolov10l_cs2) (50.0mb)
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- [yoloV10x_cs2](https://huggingface.co/Vombit/yolov10x_cs2) (61.4mb)
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## How to use
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```python
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