Which is your favorite text to image model overall?

This page summarizes the projects mentioned and recommended in the original post on /r/StableDiffusion

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  1. artroom-stable-diffusion

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  3. dalle-mini

    DALL·E Mini - Generate images from a text prompt

    Runner-ups are Craiyon (for being more "creative" than SD), Disco Diffusion, minDALL-E, and CLIP Guided Diffusion.

  4. VQGAN-CLIP

    Just playing with getting VQGAN+CLIP running locally, rather than having to use colab.

    I've screwed with many text-to-image models over the past couple of years, and I found that while I currently enjoy Stable Diffusion's coherency, I have a soft spot for the ImageNet model used by default for VQGAN+CLIP. It easily approaches the uncanny valley when generating people or animals, but makes for great abstract backgrounds and wallpapers. I already have nostalgia for generating images with it on my CPU overnight.

  5. disco-diffusion

    Runner-ups are Craiyon (for being more "creative" than SD), Disco Diffusion, minDALL-E, and CLIP Guided Diffusion.

  6. mindall-e

    PyTorch implementation of a 1.3B text-to-image generation model trained on 14 million image-text pairs

    Runner-ups are Craiyon (for being more "creative" than SD), Disco Diffusion, minDALL-E, and CLIP Guided Diffusion.

  7. CLIP-Guided-Diffusion

    Just playing with getting CLIP Guided Diffusion running locally, rather than having to use colab. (by nerdyrodent)

    Runner-ups are Craiyon (for being more "creative" than SD), Disco Diffusion, minDALL-E, and CLIP Guided Diffusion.

NOTE: The number of mentions on this list indicates mentions on common posts plus user suggested alternatives. Hence, a higher number means a more popular project.

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