# High-precision image-text matching

SigLIP 2 vision-language model trained on WebLI dataset, supporting zero-shot image classification tasks

Spec-Vision-V1 is a lightweight, state-of-the-art open-source multimodal model designed for deep integration of visual and textual data, supporting a 128K context length.

CLIPA-v2 model, an efficient contrastive image-text model, focused on zero-shot image classification tasks.

SigLIP (Sigmoid Loss for Language Image Pre-training) model trained on the WebLI dataset for zero-shot image classification tasks.