How does a sentence become an image? Not through one monolithic model — a text-to-image system is three separately-motivated trained components, wired together, and most of what a system can and can't do is a direct consequence of how they're joined.
An image and the sentence describing it are, on the surface, completely different kinds of data — a grid of pixels versus a sequence of tokens. CLIP's contribution was to train both an image encoder and a text encoder so that matching pairs land in the same embedding space, close together — and the moment that works, classification becomes a search problem, with no fixed label set required.