- Model Description - Try it Online! - Model Performance Comparison - Global Performance - Accuracy by AI Content - AI-Generated Content - Non-AI-Generated Content - Usage - Quick Start via pip - Quick Start with Pipeline - Avoid installation of pip dependency - Training - Speed and Memory Metrics This model is a vision transformer based on the **EVA architecture**, fine-tuned for **NSFW content classification**. It has been trained to detect **four categories** (neutral, low, medium, high) of visual content using **100,000 synthetically labeled images**. The model can be used as a **binary (true/false) classifier if desired, or you can obtain the full output probabilities.**. It **outperforms other excellent publicly available models** such as Falconsai/nsfw_image_detection or AdamCodd/vit-base-nsfw-detector in our internal benchmarks adding the enrichment of being able to select the NSFW level that suits your use case.

Image classification

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Monthly input tokens 10 MMonthly output tokens 2 M1 M = 1 million tokens · USD
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