AdamCodd / image-classification Open weights updated 1 year ago

vit-base-nsfw-detector

This model is a fine-tuned version of vit-base-patch16-384 on around 25000 images (drawings, photos...). It achieves the following results on the evaluation set: - Loss: 0.0937 - Accuracy: 0.9654

Params

90 M

Context

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707 K

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Commercial use: allowed apache-2.0 Not gated SAFETENSORS View on Hugging Face ↗

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daily snapshots · 106 days

▲ 87 K in the last 30 days (10.9%)

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Can you run it?

Estimated VRAM at 8K context unless noted. Pick your hardware to see the verdict per quantization.

File	Quant	Size	Est. VRAM	Verdict on RTX 4090 · 24 GB
model.safetensors	f32	0.3 GB	0.9 GB	✅ Runs comfortably

Estimate: file size × 1.1 + KV cache at 8K + 0.5 GB overhead. Not a benchmark — how we calculate this.

Specifications

Architecture: ViTForImageClassification
Parameters: 90 M
Tensor type: F32
Layers / heads: 12 / 12
Licence: apache-2.0
First seen on the Hub: 2024-01-03
Training datasets: undisclosed
AUC (reported): 0.9948
Loss (reported): 0.0937
Accuracy (reported): 0.9654
Added to our catalog: 2026-07-28

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