nsfw_image_detection
The Fine-Tuned Vision Transformer (ViT) is a variant of the transformer encoder architecture, similar to BERT, that has been adapted for image classification tasks. This specific model, named "google/vit-base-patch16-224-in21k," is pre-trained on a substantial collection of images in a supervised manner, leveraging the ImageNet-21k dataset. The images in the pre-training dataset are resized to a resolution of 224x224...
Params
90 M
Context
—
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daily snapshots · 55 days
▲ 834 K in the last 30 days (19.9%)
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6.6 M3.4 M
Jul 28Aug 15Sep 2Sep 20
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
- 2023-10-13
- Training datasets
- undisclosed
- Added to our catalog
- 2026-07-28
Compare with any image-classification model