Image Classification
ultralytics
LiteRT
Bengali
English
yolo26-cls
agriculture
bangladesh
crop-disease
yolo26
on-device
brassica
chashibhai
Instructions to use Shaq2/chashibhai-brassica-disease-cls with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ultralytics
How to use Shaq2/chashibhai-brassica-disease-cls with ultralytics:
# Couldn't find a valid YOLO version tag. # Replace XX with the correct version. from ultralytics import YOLOvXX model = YOLOvXX.from_pretrained("Shaq2/chashibhai-brassica-disease-cls") source = 'http://images.cocodataset.org/val2017/000000039769.jpg' model.predict(source=source, save=True) - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e477bcb017828eddb47d2aded4662bd0c24b083e3c88567ff02d5a6742a24010
- Size of remote file:
- 11 MB
- SHA256:
- c3632475083492be7f1d6db5601ed9cd44f1a3fecbc74d8419d4a738b83cf99e
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.