majesty-diffusion VS latent-diffusion

You missed Majesty Diffusion. It's rather complicated to use because it uses latent space diffusion and CLIP guidance at the same time, so you have to get many settings right, but once you do it can give amazing results, go see them on their Discord!

Here are a couple I've used recently:

Majestic diffusion - https://github.com/multimodalart/majesty-diffusion

Centipede diffusion - https://colab.research.google.com/github/Zalring/Centipede_D...

I suck with computers so i hope these links mean something to you, looks like devil witch magic to me. link1 link2 link3

There's also another model going around called Latent Majesty Diffusion that does the same thing.

I found the github: https://github.com/multimodalart/majesty-diffusion

Check https://github.com/multimodalart/majesty-diffusion

There is a Google Colab workbook that you can try and run for free :)

This is the image-text pairs behind: https://laion.ai/laion-400-open-dataset/

GitHub repo.

Stable Diffusion XL (SDXL) is the latest text-to-image generation model developed by Stability AI, based on the latent diffusion techniques. SDXL has the potential to create highly realistic images for media, entertainment, education, and industry domains, opening new ways in practical uses of AI imagery.

Here's a link to the early latent-diffusion git, that might be able to create a blank model (I haven't tested it): https://github.com/CompVis/latent-diffusion

Latent diffusion could work for you: https://github.com/CompVis/latent-diffusion (https://arxiv.org/abs/2112.10752)

There are a lot but the one implemented as LDSR in most stable guis is this one. https://github.com/CompVis/latent-diffusion

CompVis/latent-diffusion: High-Resolution Image Synthesis with Latent Diffusion Models (github.com)

The "retrieval based model" refers to https://github.com/CompVis/latent-diffusion#retrieval-augmen..., which uses ScaNN to train a knn embedding searcher.

Stability is basically https://github.com/CompVis/latent-diffusion + training data.

Found relevant code at https://github.com/CompVis/latent-diffusion + all code implementations here

DDIM and PLMS were the original samplers. They were part of Latent Diffusion's repository. They stand for the papers that introduced them, Denoising Diffusion Implicit Models and Pseudo Numerical Methods for Diffusion Models on Manifolds.

yes, https://github.com/CompVis/latent-diffusion