Instructions to use spicy03/vit-base-oxford-iiit-pets with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use spicy03/vit-base-oxford-iiit-pets with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="spicy03/vit-base-oxford-iiit-pets") 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("spicy03/vit-base-oxford-iiit-pets") model = AutoModelForImageClassification.from_pretrained("spicy03/vit-base-oxford-iiit-pets", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 87bb928ad8e98b748436a2626be3edc7d547b867ff145dee1f5065097a35507a
- Size of remote file:
- 343 MB
- SHA256:
- b98c1170d2d7307131bda0e10f168d66adc0274fe790dbf27b0bea61ba0b1c44
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