Siglip2 X256 Explicit Content
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Siglip2 X256 Explicit Content
Developed by prithivMLmods
A vision-language encoding model fine-tuned based on the SigLIP 2 architecture, specifically designed for multi-category image classification, particularly suitable for filtering sensitive, suggestive, or security-related media.
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Release Time : 4/29/2025
Model Overview
This model adopts the SiglipForImageClassification architecture, trained to recognize and classify content types in images, including anime images, Hentai, normal content, pornographic content, and suggestive or sexy content.
Model Features
Multi-category image classification
Capable of classifying images into five different content types, including sensitive and suggestive content.
High precision
Demonstrates high precision, recall, and F1 scores on test data, especially excelling in pornographic content detection.
Based on SigLIP 2 architecture
Utilizes the improved SigLIP 2 architecture, offering better semantic understanding and localization capabilities.
Model Capabilities
Image classification
Sensitive content detection
Adult content filtering
Multi-category recognition
Use Cases
Content moderation
NSFW content detection
Automatically detects and filters uploaded NSFW or suggestive content.
High accuracy in identifying pornographic and sexy content.
Parental control
Safe media browsing
Provides a safe browsing environment for children and teenagers by filtering inappropriate content.
Effectively identifies and filters adult content.
Dataset preprocessing
Image dataset cleaning
Automates the classification and cleaning of image datasets for research or deployment.
Rapid classification of large volumes of image data.
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