Instructions to use Vombit/yolov10l_cs2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- YOLOv10
How to use Vombit/yolov10l_cs2 with YOLOv10:
from huggingface_hub import hf_hub_download from ultralytics import YOLOv10 # pick the weights file from this repo's "Files and versions" tab weights = hf_hub_download("Vombit/yolov10l_cs2", "<weights>.pt") model = YOLOv10(weights) source = 'http://images.cocodataset.org/val2017/000000039769.jpg' model.predict(source=source, save=True) - ultralytics
How to use Vombit/yolov10l_cs2 with ultralytics:
from huggingface_hub import hf_hub_download from ultralytics import YOLOv10 # pick the weights file from this repo's "Files and versions" tab weights = hf_hub_download("Vombit/yolov10l_cs2", "<weights>.pt") model = YOLOv10(weights) source = 'http://images.cocodataset.org/val2017/000000039769.jpg' model.predict(source=source, save=True) - Notebooks
- Google Colab
- Kaggle
Download labels_correlogram.jpg from Vombit/yolov10l_cs2: direct link, hf CLI and curl.
- Browser
- Download file 235 kB
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https://huggingface.co/Vombit/yolov10l_cs2/resolve/main/labels_correlogram.jpg
- Command line
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hf download hf://Vombit/yolov10l_cs2/labels_correlogram.jpg
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curl -L -o labels_correlogram.jpg https://huggingface.co/Vombit/yolov10l_cs2/resolve/main/labels_correlogram.jpg
235 kB
