Instructions to use suredream/swin-tiny-patch4_eurosat with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use suredream/swin-tiny-patch4_eurosat with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="suredream/swin-tiny-patch4_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("suredream/swin-tiny-patch4_eurosat") model = AutoModelForImageClassification.from_pretrained("suredream/swin-tiny-patch4_eurosat", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9ab4300dab98da96d9379f4139bdb1764d5caafffa40b949d4698cf2770df844
- Size of remote file:
- 5.24 kB
- SHA256:
- 3c2b7d393887322e197eb9e0ae01b2d8dc701498dc9e7b97a440ff28ac1e327b
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