Instructions to use uralman/yolo26l-widerface with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ultralytics
How to use uralman/yolo26l-widerface with ultralytics:
from huggingface_hub import hf_hub_download from ultralytics import YOLO # pick the weights file from this repo's "Files and versions" tab weights = hf_hub_download("uralman/yolo26l-widerface", "<weights>.pt") model = YOLO(weights) source = 'http://images.cocodataset.org/val2017/000000039769.jpg' model.predict(source=source, save=True) - Notebooks
- Google Colab
- Kaggle
Download model.onnx from uralman/yolo26l-widerface: direct link, hf CLI and curl.
- Browser
- Download file 99.6 MB
-
https://huggingface.co/uralman/yolo26l-widerface/resolve/main/model.onnx
- Command line
-
hf download hf://uralman/yolo26l-widerface/model.onnx
-
curl -L -o model.onnx https://huggingface.co/uralman/yolo26l-widerface/resolve/main/model.onnx
99.6 MB
- Xet hash:
- 75f0b6a7df7f0d63816db2bcddc4a57e03ea5fb2f9c85f8920a90dbed88473f9
- Size of remote file:
- 99.6 MB
- SHA256:
- 8672c0aea1a14cc8f318ba0e999d14dcaa430543ab3caf9c369662bb0491636e
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