Instructions to use jameslahm/yolov10x with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- YOLOv10
How to use jameslahm/yolov10x with YOLOv10:
from ultralytics import YOLOvv10 model = YOLOvv10.from_pretrained("jameslahm/yolov10x") source = 'http://images.cocodataset.org/val2017/000000039769.jpg' model.predict(source=source, save=True) - Notebooks
- Google Colab
- Kaggle
Add library name (#4)
Browse files- Add library name (0d169aadba6e38d91539f4855bb1e58364a9792e)
Co-authored-by: Niels Rogge <nielsr@users.noreply.huggingface.co>
README.md
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- object-detection
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- computer-vision
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- yolov10
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datasets:
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- detection-datasets/coco
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inference: false
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- object-detection
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- computer-vision
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- yolov10
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- pytorch_model_hub_mixin
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datasets:
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- detection-datasets/coco
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library_name: yolov10
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inference: false
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