Instructions to use Konradowsky/beans-deit-tiny with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Konradowsky/beans-deit-tiny with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Konradowsky/beans-deit-tiny") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("Konradowsky/beans-deit-tiny") model = AutoModelForImageClassification.from_pretrained("Konradowsky/beans-deit-tiny", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download eval/per_class_metrics.csv from Konradowsky/beans-deit-tiny: direct link, hf CLI and curl.
- Browser
- Download file 131 Bytes
-
https://huggingface.co/Konradowsky/beans-deit-tiny/resolve/main/eval/per_class_metrics.csv
- Command line
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hf download hf://Konradowsky/beans-deit-tiny/eval/per_class_metrics.csv
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curl -L -o per_class_metrics.csv https://huggingface.co/Konradowsky/beans-deit-tiny/resolve/main/eval/per_class_metrics.csv
131 Bytes
| class,precision,recall,f1,support | |
| angular_leaf_spot,1.0,0.8837,0.9383,43 | |
| bean_rust,0.86,1.0,0.9247,43 | |
| healthy,1.0,0.9524,0.9756,42 | |