Instructions to use NSB/swin-tiny-patch4-window7-224-finetuned-eurosat-backup with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NSB/swin-tiny-patch4-window7-224-finetuned-eurosat-backup with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="NSB/swin-tiny-patch4-window7-224-finetuned-eurosat-backup") 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("NSB/swin-tiny-patch4-window7-224-finetuned-eurosat-backup") model = AutoModelForImageClassification.from_pretrained("NSB/swin-tiny-patch4-window7-224-finetuned-eurosat-backup", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5c60b06a7ceea711c8668f6206eaafcffd665aa474404210d6a0d3d66f860e76
- Size of remote file:
- 5.84 kB
- SHA256:
- 1a054afdb43841b50aab01937b1e5800a12367ba5da8bff90953dc19d016f7a8
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