A transformer over image patches that turns pictures into a sequence of visual embeddings.
Introduced inOct 2020An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale
The vision tower of a multimodal model is usually a ViT-family encoder (SigLIP and CLIP variants dominate) pretrained on image-text pairs. It converts patch embeddings into contextualized visual features that a projector then aligns with the language model’s embedding space. Multimodal capability lives or dies by this component and how it was pretrained.
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