Instructions to use HorcruxNo13/swin-tiny-patch4-window7-224 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HorcruxNo13/swin-tiny-patch4-window7-224 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="HorcruxNo13/swin-tiny-patch4-window7-224") 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("HorcruxNo13/swin-tiny-patch4-window7-224") model = AutoModelForImageClassification.from_pretrained("HorcruxNo13/swin-tiny-patch4-window7-224") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d6c304a6abb4c67aba856f9c76b2fa5d4190fb4f29f4bdddf57f5e5512daa3de
- Size of remote file:
- 4.09 kB
- SHA256:
- 4c65c717272eaaf96c5bf910ae2ffddb125d47dbf1e8a7b421de93e681c21d85
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