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RESISC45-SigLIP2 is a vision-language encoder model fine-tuned from google/siglip2-base-patch16-224 for multi-label image classification. It is specifically trained to recognize and tag multiple land use and land cover scene categories from the RESISC45 dataset using the SiglipForImageClassification architecture.
SAT-Landforms-Classifier is an image classification vision-language encoder model fine-tuned from google/siglip2-base-patch16-224 for a single-label classification task. It is designed to classify satellite images into different landform categories using the SiglipForImageClassification architecture