InvokeAI VS fast-stable-diffusion

Probably not, since I have no idea what you're talking about. I've just been using the models that InvokeAI (2.3, I only just now saw there's a 3.0) downloads for me [0]. The SD1.5 one is as good as ever, but the SD2 model introduces artifacts on (many, but not all) faces and copyrighted characters.

[0] https://github.com/invoke-ai/InvokeAI

I actually used the rocm/pytorch image you also linked.

I'm not sure what you're pointing to with your reference to the Fedora-based images. I'm quite happy with my NixOS install and really don't want to switch to anything else. And as long as I have the correct kernel module, my host OS really shouldn't matter to run any of the images.

And I'm sure it can be made to work with many base images, my point was just that the dependency management around pytorch was in a bad state, where it is extremely easy to break.

> Anyways, hopefully this PR fixes the immediate issue: https://github.com/invoke-ai/InvokeAI/pull/5714/files

It does! At least for me. It is my PR after all ;)

The data being flagged is not in that github repo, it's fetched from elsewhere and I don't fancy spending time looking for it. The alert is for 'Sirefef!cfg' which has been reported as a false positive with a bunch of other stable diffusion projects (https://www.reddit.com/r/StableDiffusion/comments/101zjec/trojanwin32sirefefcfg_an_apparently_common_false/, https://www.reddit.com/r/StableDiffusion/comments/xmhukb/trojan_in_waifudiffusion_model_file/, https://github.com/invoke-ai/InvokeAI/issues/2773 )

I haven’t tried it recently, but InvokeAI runs on Mac. Invoke. I used to run on my MacBook, but have since gotten a Win laptop.

There are already a number of local, inference options that are (crucially) open-source, with more robust feature sets.

And if the defense here is "but Auto1111 and Comfy don't have as user-friendly a UI", that's also already covered. https://github.com/invoke-ai/InvokeAI

https://github.com/invoke-ai/InvokeAI should work on your machine. For LLM models, the smaller ones should run using llama.cpp, but I don't think you'll be happy comparing them to ChatGPT.

Stable Diffusion. /r/stablediffusion There are many tutorials on how to set it up locally and use it. InvokeAI is the easiest way to set it up. https://github.com/invoke-ai/InvokeAI

InvokeAI

I tried using TheLastBen's fast dreambooth trainer. I managed to train a ckpt file but I can't run it.

You have a colab from ThelastBen It uses to be thes best at the time when auto1111 was working in google colab free. https://github.com/TheLastBen/fast-stable-diffusion

Using https://github.com/TheLastBen/fast-stable-diffusion

This repo offers a template how to start with SD on runpod https://github.com/TheLastBen/fast-stable-diffusion. But I know how to code, si I made my own solution.

I can confirm I'm using the latest version of the colab notebook of this repo (https://github.com/TheLastBen/fast-stable-diffusion). Anyone can point to any solutions to this problem? Thanks in advance!

TheLastBen's Fast DB SD Colabs, +25-50% speed increase, AUTOMATIC1111 + DreamBooth

CalledProcessError Traceback (most recent call last) in () 182 wget.download('https://github.com/TheLastBen/fast-stable-diffusion/raw/main/Dreambooth/det.py') 183 print('Detecting model version...') --> 184 Custom_Model_Version=check_output('python det.py '+sftnsr+' --MODEL_PATH '+MODEL_PATH, shell=True).decode('utf-8').replace('\n', '') 185 clear_output() 186 print(''+Custom_Model_Version+' Detected')

have you tried https://github.com/TheLastBen/fast-stable-diffusion ?