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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 79b67d7b61c5f16cf0d277fd4ba4cf6e89e1f0c35b76b22c0e4cf748d09430d9
- Size of remote file:
- 4.6 kB
- SHA256:
- d6716335dd4543496ff2707a910b9c4ff455a553e69d03150c59199f0152c3f8
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