Instructions to use AmitMidday/Dogs-Breed-Classification-Using-Vision-Transformers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AmitMidday/Dogs-Breed-Classification-Using-Vision-Transformers with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="AmitMidday/Dogs-Breed-Classification-Using-Vision-Transformers") 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("AmitMidday/Dogs-Breed-Classification-Using-Vision-Transformers") model = AutoModelForImageClassification.from_pretrained("AmitMidday/Dogs-Breed-Classification-Using-Vision-Transformers") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b84b5af856ba995ffa9b283457ad2e5f7a961fb9be19ffac32d2164cdc189c90
- Size of remote file:
- 687 MB
- SHA256:
- 61dc2150458440137b8b17b775b2ee3bfc31048c85444078d3d4f730b9726dcf
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