# nsfw_image_detection by Falcons.ai: Open-Weight Model Source: https://savrn.com/models/nsfw-image-detection Markdown alternate of the page above; the site index is https://savrn.com/llms.txt --- ## Runs On What it takes to serve nsfw_image_detection (86M parameters): the memory its weights need at each precision, and the cheapest way to rent enough data-center GPUs to hold them. | Precision | Weights | Memory needed | Cheapest setup | Per hour | Also fits | | --- | --- | --- | --- | --- | --- | | 16-bit | 0.2 GB | 0.2 GB | 1x [MI300X](https://savrn.com/ai-index/pricing/gpus/mi300x) (192 GB) Vultr | $1.85 | [1x H100](https://savrn.com/ai-index/pricing/gpus/h100) $1.99 · [1x MI325X](https://savrn.com/ai-index/pricing/gpus/mi325x) $2.00 | | 8-bit | 0.1 GB | 0.1 GB | 1x [MI300X](https://savrn.com/ai-index/pricing/gpus/mi300x) (192 GB) Vultr | $1.85 | [1x H100](https://savrn.com/ai-index/pricing/gpus/h100) $1.99 · [1x MI325X](https://savrn.com/ai-index/pricing/gpus/mi325x) $2.00 | | 4-bit | 0.0 GB | 0.1 GB | 1x [MI300X](https://savrn.com/ai-index/pricing/gpus/mi300x) (192 GB) Vultr | $1.85 | [1x H100](https://savrn.com/ai-index/pricing/gpus/h100) $1.99 · [1x MI325X](https://savrn.com/ai-index/pricing/gpus/mi325x) $2.00 | Memory is the weights at that precision plus 20% for the runtime and a short context; a long context needs more. Prices are the lowest on-demand hourly rates in the [SAVRN Index](https://savrn.com/ai-index/pricing/gpus), read Oct 23, 2026. [nsfw_image_detection on every accelerator the SAVRN Index prices, at every precision](https://savrn.com/models/nsfw-image-detection/gpus) ## SAVRN's Notes on nsfw_image_detection An 86M-parameter ViT fine-tune — the card names google/vit-base-patch16-224-in21k, ImageNet-21k pretraining, 224×224 input — for NSFW image screening. The repo carries 1.5 GB of float32 in bin, pt and safetensors copies; at 16-bit the model needs 0.2 GB and at 4-bit effectively nothing. The $1.85-an-hour MI300X in the Runs On table is a formality: this belongs on a CPU next to your upload pipeline, and 2.2M monthly downloads suggest exactly that use. Apache 2.0 permits commercial moderation use with notices kept, and no host on our Index prices it per token. Treat it as a first-pass filter, not a decision-maker: single-label ViT classifiers age fast, and while the repo was updated 2026-09-07, the architecture is a 2020 design. Calibrate the threshold on your own data before trusting the default operating point — the card describes the model, not its precision and recall. SAVRN Research ## Model Card By Falcons.ai, published under apache-2.0, revision 96cb0d0342c7. ### Model Card: Fine-Tuned Vision Transformer (ViT) for NSFW Image Classification ### Model Description 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 pixels, making it suitable for a wide range of image recognition tasks. During the training phase, meticulous attention was given to hyperparameter settings to ensure optimal model performance. The model was fine-tuned with a judiciously chosen batch size of 16. This choice not only balanced computational efficiency but also allowed for the model to effectively process and learn from a diverse array of images. [Read the full model card (1,289 words)](https://savrn.com/models/nsfw-image-detection/card) ## Configuration Architecture ViTForImageClassification Layers 12 Hidden size 768 Feed-forward size 3,072 Attention heads 12 Stored precision float32 Model type vit ## Identity and Version Repository Falconsai/nsfw_image_detection Publisher Falcons.ai Task Image classification Modality Image Library transformers Parameters 86M parameters Languages vit Revision 96cb0d0342c7afb80cab76ecc58b265fa44da256 First published 2023-10-13 Last updated 2026-09-07 ## Files and Weights 9 files, 1.5 GB in total. The weights are 4 files totalling 1.5 GB in bin, pt, safetensors. Weights4 files · 1.5 GB Configuration3 files · 1.1 KB Documentation1 file · 10.6 KB Repository1 file · 1.5 KB Every file | File | Type | Size | SHA-256 | | --- | --- | --- | --- | | falconsai_yolov9_nsfw_model_quantized.pt | Weights | 87.1 MB | ad6659b81050 | | model.safetensors | Weights | 343.2 MB | 97b2ce64ec14 | | optimizer.pt | Weights | 686.5 MB | 02ff26c6fe3d | | pytorch_model.bin | Weights | 343.3 MB | 2a6b06faec56 | | config.json | Configuration | 724 B | — | | labels.json | Configuration | 38 B | — | | preprocessor_config.json | Configuration | 325 B | — | | README.md | Documentation | 10.6 KB | — | | .gitattributes | Repository | 1.5 KB | — | ## License and Download License apache-2.0 Access Open weights, no gate Download size 1.5 GB [Download from Falcons.ai](https://huggingface.co/Falconsai/nsfw_image_detection) Released by Falcons.ai through its official repository on Hugging Face. [Read the license](https://www.apache.org/licenses/LICENSE-2.0). ## Built From - Described by [arXiv:2010.11929](https://savrn.com/papers/an-image-is-worth-16x16-words-transformers-for-image-recognition-at-scale) ## Memory Requirements | Precision | Weights in memory | | --- | --- | | As published | 1.5 GB | | 16-bit | 0.2 GB | | 8-bit | 0.1 GB | | 4-bit | 0.0 GB | Weights only, from the published parameter count; the key-value cache and runtime add to this. ## Compare nsfw_image_detection - [nsfw_image_detection vs rorshark-vit-base](https://savrn.com/models/compare/nsfw-image-detection-vs-rorshark-vit-base) - [gender-classification-2 vs nsfw_image_detection](https://savrn.com/models/compare/gender-classification-2-vs-nsfw-image-detection) - [gender-classification vs nsfw_image_detection](https://savrn.com/models/compare/gender-classification-vs-nsfw-image-detection) ## Questions About nsfw_image_detection ### How much GPU memory does nsfw_image_detection need? About 0.2 GB at 16-bit and 0.1 GB at 4-bit: the weights (86M parameters) plus a working margin. A long context needs more. ### What is the cheapest GPU to run nsfw_image_detection on? At 16-bit, 1x MI300X from $1.85 an hour; at 4-bit, 1x MI300X from $1.85 an hour, at the lowest on-demand prices the SAVRN Index lists. ### Can I use nsfw_image_detection commercially? Yes. nsfw_image_detection is released under Apache License 2.0. The Apache License 2.0 is a permissive open-source license. It permits commercial use, modification and redistribution. It requires keeping the license and copyright notices and any NOTICE file, stating significant changes, and it includes an express patent grant from contributors. ## Similar Models Model · Image classification ### [gender-classification](https://savrn.com/models/gender-classification) [Rizvan Dwikifirdaus](https://savrn.com/model-publishers/rizvandwiki) Autogenerated by HuggingPics Create your own image classifier for anything by running the demo on Google Colab. Report any issues with the demo at the github repo. Open weights 86M parameters transformers [View model](https://savrn.com/models/gender-classification) Model · Image classification ### [rorshark-vit-base](https://savrn.com/models/rorshark-vit-base) [Chester Enright](https://savrn.com/model-publishers/amunchet) This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the imagefolder dataset. 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Open weights 86M parameters transformers [View model](https://savrn.com/models/gender-classification-2) Model · Image classification ### [nsfw-classifier](https://savrn.com/models/nsfw-classifier) [Giacomo Arienti](https://savrn.com/model-publishers/giacomoarienti) In today's digital world, user-generated content is a double-edged sword. While it fosters creativity and engagement, it also opens the door to inappropriate or illegal content being shared. Our NSFW Image Classifier is specifically designed to identify and filter out explicit images, including pornography, hentai, and sexually suggestive content, ensuring your platform remains safe, secure, and legally compliant. With more than 2M downloads, our NSFW Image Classifier has become the go-to solution for platforms looking to maintain a clean and safe environment for their users. Many developers and companies have already chosen our solution to protect their communities—will you be next? 1.… Open weights cc-by-nc-nd-4.0 86M parameters transformers [View model](https://savrn.com/models/nsfw-classifier) Model · Image classification ### [fairface_age_image_detection](https://savrn.com/models/fairface-age-image-detection) [Dmytro Iakubovskyi](https://savrn.com/model-publishers/dima806) Detects age group with about 59% accuracy based on an image. See https://www.kaggle.com/code/dima806/age-group-image-classification-vit for details. Open weights apache-2.0 86M parameters transformers [View model](https://savrn.com/models/fairface-age-image-detection) Model · Image classification ### [vit-age-classifier](https://savrn.com/models/vit-age-classifier) [Nate Raw](https://savrn.com/model-publishers/nateraw) A vision transformer finetuned to classify the age of a given person's face. Open weights 86M parameters transformers [View model](https://savrn.com/models/vit-age-classifier) ## Falcons.ai [All models and datasets](https://savrn.com/model-publishers/falconsai) ## Versions - [96cb0d0342c7](https://savrn.com/models/nsfw-image-detection/versions/96cb0d0342c7) · current 2026-10-23 ## Explore More - [All image classification models](https://savrn.com/models/tasks/image-classification) - [All models under apache-2.0](https://savrn.com/models/licenses/apache-2-0) - [Model comparisons](https://savrn.com/models/comparisons) - [The model directory](https://savrn.com/models) - [Open model prices by host](https://savrn.com/ai-index/pricing/open-models) ## Source - Repository metadata, read 2026-10-19. - [Hugging Face record](https://huggingface.co/Falconsai/nsfw_image_detection) - [How the hub is built](https://savrn.com/model-hub/methodology)