/majesty-diffusion

Majesty Diffusion by @Dango233(@Dango233max) and @apolinario (@multimodalart)

Primary LanguageJupyter Notebook

Majesty Diffusion 👑

Generate images from text with majesty

Formerly known as Princess Generator

Majesty Diffusion are implementations of text-to-image diffusion models with a royal touch 👸

Access our Majestic Guide (under construction), join our community on Discord or reach out via @multimodalart on Twitter). Also share your settings with us

Current implementations:

Latent Majesty Diffusion v1.6

Formerly known as Latent Princess Generator

Open In Colab

A Dango233 and apolinario (@multimodalart) Colab notebook implementing CompVis' Latent Diffusion. Contribute to our settings library on Hugging Face!

v1.2
v1.3 - Better Upscaler (learn how to use it on our [Majestic Guide](https://multimodal.art/majesty-diffusion))
v1.4 & 1.5 & 1.6

v1.4

  • Added Dango233 Customised Dynamic Thresholding
  • Added open_clip ViT-L/14 LAION-400M trained
  • Fix CLOOB perceptor from MMC
  • Removes latent upscaler (was broken), adds RGB upscaler

v1.5

  • Even better defaults
  • Better dynamic thresholidng
  • Improves range scale
  • Adds var scale and mean scale
  • Adds the possibility of blurring cuts
  • Adds experimental compression and punishment settings
  • Adds PLMS support (experimental, results perceptually weird)

v1.6

  • Adds LAION ongo (finetuned in artworks) and erlich (finetuned for making logos) models
  • Adds noising and scaling during the advanced schedulign phases
  • Adds ViT-L conditioning downstream to the Latent Diffusion unet process
  • Small tweaks on dynamic thresholding
  • Fixes linear ETA

V-Majesty Diffusion v1.2

Formerly known as Princess Generator ver. Victoria

Open In Colab

A Dango233 and apolinario (@multimodalart) Colab notebook implementing crowsonkb's V-Objective Diffusion, with the following changes:

TODO

Please feel free to help us in any of these tasks!

  • Figure out better defaults and add more settings to the settings library (contribute with a PR!)
  • Add all notebooks to a single pipeline where on model can be the output of the other (similar to Centipede Diffusion)
  • Add all notebooks to the MindsEye UI
  • Modularise everything
  • Create a command line version
  • Add an inpainting UI
  • Improve performance, both in speed and VRAM consumption
  • More technical issues will be listed on https://github.com/multimodalart/majesty-diffusion/issues

Acknowledgments

Some functions and methods are from various code masters - including but not limited to advadnoun, crowsonkb, nshepperd, russelldc, Dango233 and many others