Prior Transformer The Prior Transformer was originally introduced in Hierarchical Text-Conditional Image Generation with CLIP Latents by Ramesh et al. It is used to predict CLIP image embeddings from CLIP text embeddings; image embeddings are predicted through a denoising diffusion process. The abstract from the paper is: Contrastive models like CLIP have been shown to learn robust representations of images that capture both semantics and style