Instructions to use microsoft/swin-small-patch4-window7-224 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use microsoft/swin-small-patch4-window7-224 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="microsoft/swin-small-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-small-patch4-window7-224") model = AutoModelForImageClassification.from_pretrained("microsoft/swin-small-patch4-window7-224") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6e128d8ef1837953f5ffce649acb09e250b788b309b3b74188aaf4ceb5623fc2
- Size of remote file:
- 199 MB
- SHA256:
- c17c4edf3230695f4de854105601b1adb96e737d77a9a8b718010c8a103fc7e5
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