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:
- d57025c88cc4ee5deb2ede3f25b7c49567a0c71006642af1098acef8038347a9
- Size of remote file:
- 344 MB
- SHA256:
- b457578c69a0d6037b27f9d16d4e04a1d2b2c842308bb3fae047656d116054ee
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