unprompted VS distributed-diffusion

I'm pleased to announce the release of Unprompted v10.0.0, the Swiss Army knife extension for A1111. This is a major update that brings a number of new features and improvements, including:

Unprompted: https://github.com/ThereforeGames/unprompted

you can get the same effect with unprompted zoom enhance feature. just paste this into the prompt field.

It's been a while since my last Unprompted post, so I wanted to share some of the new things you can do with this extension. 🙂

Also if you're curious, check out the Unprompted extension's implementation of img2pez for a1111 in img2img. Basic gist is that it uses machine learning to examine the image and tries to find tokens that would likely produce that image. I've found it to be pretty far off the mark most the time, but the terms it gives you can actually be quite useful.

There's a feature in unprompted that does this.

One thing to consider: there is an extension that will let you write some scripts as prompts, and it extends what you can do with wildcards. https://github.com/ThereforeGames/unprompted.git

Solution for 9.2.0: Use modified https://github.com/ThereforeGames/unprompted/issues/84 you posted. This made a stitch image in %TEMP% and had the modified image displayed in Auto1111 GUI. Only reason I am @ing is because if I had this issue on 9.2.0 I'm sure others are. I had to use FULL shortcode in wizard zoom enhance section; I had to use FULL shortcode in wizard zoom enhance section; [if batch_index=0][after][zoom_enhance show_original mask='face' replacement='[insert prompt]' mask_sort_method='left-to-right' upscale_method='Nearest Neighbor' downscale_method='Lanczos' blur_size=0.03 cfg_scale_min=3.0 denoising_max=0.65 mask_size_max=0.3 mask_method='clipseg' sharpen_amount=1.0 color_correct_method='none' color_correct_timing='pre' color_correct_strength=1.0 min_area=50.0 contour_padding=0.0 upscale_width=512.0 upscale_height=512.0 hires_size_max=1024.0][/after][/if]

It was a long time ago I used it but I think it takes some learning I would suggest reading the starter guide the short code relates to the extra detail but you need to learn how to write it I'm pretty sure there is a built in helper sorry I haven't used it extensively there must be a video guide on YouTube too there is for almost all of this ai stuff https://github.com/ThereforeGames/unprompted/blob/main/docs/GUIDE.md

And the updated extension here: https://github.com/ThereforeGames/unprompted

noob here, dunno nothing about how community could contribute be reinforcing a shared training but this is maybe what we should aim. Imagin users contributing in training a large models, with a system of upvotes like midjourney)... They have control over the model and reionforcing that. We are fragmented in multiple models, loras and such. Everyone focusin on different things. Made some researches time ago and ended up here: https://github.com/chavinlo/distributed-diffusion and this https://learning-at-home.github.io/

Yes, hivemind trained a gpt 6B model like this.

General model training https://github.com/learning-at-home/hivemind

Stable diffusion specific https://github.com/chavinlo/distributed-diffusion

Inference only stable diffusion https://stablehorde.net/

Github Repo: https://github.com/chavinlo/distributed-diffusion

There has been some effort to train diffusion on distributed community hardware. Mainly https://github.com/chavinlo/distributed-diffusion it is based on https://learning-at-home.github.io/ . If this takes off then we can train stable diffusion together as a community without relying on any company.

If you want to try it on your own, you can check the repo https://github.com/chavinlo/distributed-diffusion or the discord https://discord.gg/xVsyrmhQWS