Post
3065
Introducing Image-Guard-2.0, an experimental, lightweight vision-language encoder model with a size of 0.1B (<100M parameters), trained on SigLIP2 (siglip2-base-patch16-224). Designed for multi-label image classification tasks, this model functions as an image safety system, serving as an image guard or moderator across a wide range of categories, from anime to realistic imagery.
⚡blog-article: https://huggingface.co/blog/prithivMLmods/image-guard-models
It also performs strict moderation and filtering of artificially synthesized content, demonstrating strong detection and handling of explicit images. Image-Guard-2.0 delivers robust performance in streamlined scenarios, ensuring reliable and effective classification across diverse visual inputs.
⚡blog-article: https://huggingface.co/blog/prithivMLmods/image-guard-models
It also performs strict moderation and filtering of artificially synthesized content, demonstrating strong detection and handling of explicit images. Image-Guard-2.0 delivers robust performance in streamlined scenarios, ensuring reliable and effective classification across diverse visual inputs.