Instructions to use ahishamm/vit-base-isic-sharpened-patch-32 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ahishamm/vit-base-isic-sharpened-patch-32 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="ahishamm/vit-base-isic-sharpened-patch-32") 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("ahishamm/vit-base-isic-sharpened-patch-32") model = AutoModelForImageClassification.from_pretrained("ahishamm/vit-base-isic-sharpened-patch-32") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
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by SFconvertbot - opened
- model.safetensors +3 -0
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version https://git-lfs.github.com/spec/v1
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oid sha256:02c2552ec86ae30599e61ad050140cc2b455e1529e7ee8a3b0d0c7da7b5b3ca2
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size 349853372
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