Instructions to use ayoubkirouane/VIT_Beans_Leaf_Disease_Classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ayoubkirouane/VIT_Beans_Leaf_Disease_Classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="ayoubkirouane/VIT_Beans_Leaf_Disease_Classifier") 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("ayoubkirouane/VIT_Beans_Leaf_Disease_Classifier") model = AutoModelForImageClassification.from_pretrained("ayoubkirouane/VIT_Beans_Leaf_Disease_Classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e75926a51a342e41a35d525e3e286b3cd37d90a3c7321caf60cd16b6c52b832d
- Size of remote file:
- 343 MB
- SHA256:
- 4967aa7e0f96d3cb53af7b4843cd22db259c5e06b67dcf932305d49400743055
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.