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")# pip install -U transformers accelerate # 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
Download checkpoint-12705/training_args.bin from dima806/cat_breed_image_detection: direct link, hf CLI and curl.
- Browser
- Download file 4.67 kB
-
https://huggingface.co/dima806/cat_breed_image_detection/resolve/main/checkpoint-12705/training_args.bin
- Command line
-
hf download hf://dima806/cat_breed_image_detection/checkpoint-12705/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/dima806/cat_breed_image_detection/resolve/main/checkpoint-12705/training_args.bin
4.67 kB
- Xet hash:
- ae4d51ae849e1dfc5f8ccee22cf410322cefcc6d8cf9ca97612742547a4fdb39
- Size of remote file:
- 4.67 kB
- SHA256:
- 24da8bd5bb13554ebf9715f0be1eeb363ad49be1a9401f1cc192f372ad85a4cd
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