<ul><li>Vision-language models (VLMs) are designed to handle tasks involving visual and textual data such as describing images and generating text based on images.</li><li>Most VLMs use transformer-based architectures adapted to process both pixel data and token-based text.</li><li>Dual-encoder models in VLMs use separate neural networks for processing images and text to align embeddings in a shared latent space.</li><li>One popular dual-encoder model, OpenAI’s CLIP, uses transformer-based text encoder and a vision encoder like ResNet or ViT for image processing.</li></ul>

Using Vision-Language Models

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