text-to-text-transfer-tra VS latent-diffusion

T5 was open-sourced on release (up to 11B params): https://github.com/google-research/text-to-text-transfer-tra...

It is also available via Hugging Face transformers.

Unclear if 11B is the T5-XXL mentioned in the paper, however.

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