Instructions to use bryanzhou008/swin-tiny-patch4-window7-224-finetuned-eurosat with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bryanzhou008/swin-tiny-patch4-window7-224-finetuned-eurosat with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="bryanzhou008/swin-tiny-patch4-window7-224-finetuned-eurosat") 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("bryanzhou008/swin-tiny-patch4-window7-224-finetuned-eurosat") model = AutoModelForImageClassification.from_pretrained("bryanzhou008/swin-tiny-patch4-window7-224-finetuned-eurosat", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ae10d1bcd20b81ebe361a6a91c72856e24c28cc9998a127f4fb1dc083f45307e
- Size of remote file:
- 5.24 kB
- SHA256:
- f11696d7308bb289a090175df7dc4bf8b055773e8bef5030eaf2008394e7862c
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