Instructions to use dima806/cat_breed_image_detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dima806/cat_breed_image_detection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="dima806/cat_breed_image_detection") 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("dima806/cat_breed_image_detection") model = AutoModelForImageClassification.from_pretrained("dima806/cat_breed_image_detection") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9ffe3b628c308bbdcd3a3c93c8247b198a57b9ebe9d8fb669f1cd36f3f758823
- Size of remote file:
- 4.67 kB
- SHA256:
- c46896dc6ce144fbab9a60698cf84ee21a3b90e77075f2c78a48583bfaf515f3
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