Instructions to use Adit-jain/soccana with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ultralytics
How to use Adit-jain/soccana 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("Adit-jain/soccana", "<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/P_curve.png from Adit-jain/soccana: direct link, hf CLI and curl.
- Browser
- Download file 141 kB
-
https://huggingface.co/Adit-jain/soccana/resolve/main/Model/P_curve.png
- Command line
-
hf download hf://Adit-jain/soccana/Model/P_curve.png
-
curl -L -o P_curve.png https://huggingface.co/Adit-jain/soccana/resolve/main/Model/P_curve.png
141 kB

- Xet hash:
- 9081391e7129948a046f6a86d27b019856d0e1edd01f7491c8a96ef892a7103d
- Size of remote file:
- 141 kB
- SHA256:
- f034dd07e3cbe91ca598473eaa5401450836abf632df04db433860ee66a9da9f
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