Instructions to use AlessandroFerrante/StreetSignSenseY12m with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ultralytics
How to use AlessandroFerrante/StreetSignSenseY12m with ultralytics:
from ultralytics import YOLOvv12 model = YOLOvv12.from_pretrained("AlessandroFerrante/StreetSignSenseY12m") source = 'http://images.cocodataset.org/val2017/000000039769.jpg' model.predict(source=source, save=True) - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fd95b32cd73606cb8826f0df11c7c509dc5d5983244a623a3cba67163434662b
- Size of remote file:
- 81.4 MB
- SHA256:
- 1f73a8d3f74583d2cb2f658f8234b46835f90d8eb5bf8a932a394b1263697ba6
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.