Instructions to use microsoft/swin-large-patch4-window7-224 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use microsoft/swin-large-patch4-window7-224 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="microsoft/swin-large-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("microsoft/swin-large-patch4-window7-224") model = AutoModelForImageClassification.from_pretrained("microsoft/swin-large-patch4-window7-224") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9d54205157628a850dc5659a7e4febcd157ab9cd19087c88f699039c22d1b760
- Size of remote file:
- 787 MB
- SHA256:
- 93ed51cd713c36a1b4227cbe585261fac0df1f2d2e011669cf6389c714ac0dc5
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