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:
- 269b5a9d92694893845a08dd0f19732f8613561e787a5492e73a9e1932417317
- Size of remote file:
- 687 MB
- SHA256:
- e2abcd237a6a6537467f9e7c25e532002cf7efa9887fcf436e91007c2d764818
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