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nsfw-classifier

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vit-mini-explicit-content is an image classification vision-language model fine-tuned from vit-base-patch16-224-in21k for a single-label classification task. It categorizes images based on their explicitness using the ViTForImageClassification architecture.

  • Updated May 20, 2025
  • Python

nsfw-image-detection is a vision-language encoder model fine-tuned from siglip2-base-patch16-256 for multi-class image classification. Built on the SiglipForImageClassification architecture, the model is trained to identify and categorize content types in images, especially for explicit, suggestive, or safe media filtering.

  • Updated May 12, 2025
  • Python

siglip2-mini-explicit-content is an image classification vision-language encoder model fine-tuned from siglip2-base-patch16-512 for a single-label classification task. It is designed to classify images into categories related to explicit, sensual, or safe-for-work content using the SiglipForImageClassification architecture.

  • Updated May 20, 2025
  • Python

nsfw-image-detection is a vision-language encoder model fine-tuned from siglip2-base-patch16-256 for multi-class image classification. Built on the SiglipForImageClassification architecture, the model is trained to identify and categorize content types in images, especially for explicit, suggestive, or safe media filtering.

  • Updated May 17, 2025
  • Python

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