# SigLIP Vision Encoder

A vision-language model based on the SigLIP image encoder, utilizing global average pooling, suitable for multimodal tasks.

A vision Transformer model based on SigLIP, containing only the image encoder, using original attention pooling, suitable for image feature extraction tasks.

Vision Transformer model based on SigLIP, containing only the image encoder part, using original attention pooling mechanism

Vision Transformer model based on SigLIP, containing only the image encoder part, utilizing original attention pooling mechanism

nanoLLaVA-1.5 is a vision-language model with under 1 billion parameters, designed specifically for edge devices—compact yet powerful.