Instructions to use RKoops/BeanLeafClassifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use RKoops/BeanLeafClassifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="RKoops/BeanLeafClassifier") 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("RKoops/BeanLeafClassifier") model = AutoModelForImageClassification.from_pretrained("RKoops/BeanLeafClassifier") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9f1c7be948bba672cea837ff1aebecb14dd603be0ca9eb45c2925ba46946fc4b
- Size of remote file:
- 343 MB
- SHA256:
- 0766e1e3966c731734d8c9fe8973bd52cbbd3b7ec8ace1383bee0b0efe0a3512
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