Instructions to use microsoft/swin-tiny-patch4-window7-224 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use microsoft/swin-tiny-patch4-window7-224 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="microsoft/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("microsoft/swin-tiny-patch4-window7-224") model = AutoModelForImageClassification.from_pretrained("microsoft/swin-tiny-patch4-window7-224") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c9ee5c51edb423376ff8b156185faf1ef6db26718973138396c72f0f0175e215
- Size of remote file:
- 113 MB
- SHA256:
- a941acf68a76b365d67738d6c6dce4f0db3ea5224b7cff856d3f8f3753502d29
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