guided-diffusion VS glid-3-xl-stable

People who made these colabs better and better also the same people who are at Midjourney now. But the "mother" of it all, was Katherine Crowson. She made a fine tuned model that uses a 512x512 unconditional ImageNet diffusion model fine-tuned from OpenAI's 512x512 class-conditional ImageNet diffusion model (https://github.com/openai/guided-diffusion) together with CLIP (https://github.com/openai/CLIP) to connect text prompts with images. It uses a smaller secondary diffusion model trained by Katherine Crowson to remove noise from intermediate timesteps to prepare them for CLIP.

I am trying to use OpenAI's Guided Diffusion Github to train my own diffusion model. I thought to ask here to see if anyone had any experience with it as I've been having trouble training my own models on it. If anyone has any resources to point me towards it would be greatly appreciated!

Our codebase for the diffusion models builds heavily on OpenAI's ADM codebase , lucidrains, Stable Diffusion, Lightning and Hugging Face. Thanks for open-sourcing!

I am working with guided diffusion. I would like to reproduce the results of the repository for the 64->256 super resolution network. https://github.com/openai/guided-diffusion

this code is (mostly) just the original openai guided diffusion code: https://github.com/openai/guided-diffusion

Starting resource, as it is all done through this code (information on how to do it on Colab is out there) https://github.com/openai/guided-diffusion

Original notebook by Katherine Crowson (https://github.com/crowsonkb, https://twitter.com/RiversHaveWings). It uses either OpenAI's 256x256 unconditional ImageNet or Katherine Crowson's fine-tuned 512x512 diffusion model (https://github.com/openai/guided-diffusion), together with CLIP (https://github.com/openai/CLIP) to connect text prompts with images.

Code for https://arxiv.org/abs/2105.05233 found: https://github.com/openai/guided-diffusion

Paper, repo, Colab. It's really good.

I don't know how you can say this but it's completely different than anything we had before, the only exception was https://github.com/Jack000/glid-3-xl-stable/wiki/Custom-inpainting-model, this model was a finituned version of v1.4 but not having a separate channel for the original image and the mask makes it weaker.

Check out the item by lkwq007 in this list https://www.reddit.com/r/StableDiffusion/comments/wqaizj/list_of_stable_diffusion_systems/ , and also the model for this web app https://replicate.com/devxpy/glid-3-xl-stable , which I believe is this https://github.com/Jack000/glid-3-xl-stable .

Right now I am using different, better optimized model for just outpaiting/inpating using this https://github.com/Jack000/glid-3-xl-stable as base

I'm using a slightly modified and optimized version of https://github.com/Jack000/glid-3-xl-stable for inpainting/outpainting.

For this editor we've integrated Jack Qiao's excellent custom inpainting model from the glid-3-xl-sd project instead. This is a fine-tuned version of Stable Diffusion with significantly better inpainting capabilities than standard SD. You can read more about how it works here along with comparison images between it and regular SD.

you cant. they are different architectures: https://github.com/Jack000/glid-3-xl-stable/issues/17

I am wondering tho, if this one uses https://github.com/Jack000/glid-3-xl-stable/wiki/Custom-inpainting-model glid-3 inpainting?

(also check this custom SD inpainting/outpainting model, it's easily the best i've seen https://github.com/Jack000/glid-3-xl-stable/wiki/Custom-inpainting-model)