Instructions to use Sohaibsoussi/vit-beans_leaves_disease with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sohaibsoussi/vit-beans_leaves_disease with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Sohaibsoussi/vit-beans_leaves_disease") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("Sohaibsoussi/vit-beans_leaves_disease") model = AutoModelForImageClassification.from_pretrained("Sohaibsoussi/vit-beans_leaves_disease") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a5e970cbb943278b378d7e9bf913f71e3cd34cfa39c2f2a2ac918c4c5f966f58
- Size of remote file:
- 343 MB
- SHA256:
- 2fc0040921a48c9587b5b04318a1926c5dc4e2f9c6732d77d0c44eb39621202e
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.