reover, the joint embedding space of CLIP enables language-guided image manipulations in a zero-shot fashion. We use diffusion models for the decoder and experiment with both autoregressive and diffusion models for the prior, finding that the latter are computationally more efficient and produce higher-quality samples. You can find lucidrains’ DALL-E 2 recreation at lucidrains/DALLE2-pytorch. Make sure to check out the Schedulers guide to learn