InvokeAI VS merge-models

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

Merging models takes a lot of memory and 16 GB isn't that much these days. So getting 8 or 16 more GB wouldn't be a bad idea. Can you merge 2 models? If you need to merge more than 2 maybe you could do it in stages to save memory. You could also try adapting a standalone script to merge them without loading webui.

Yes, VAEs can be merged. In fact, most scripts capable of merging checkpoints should work as-is with VAEs, since they're fundamentally very similar. Try using this script while specifying VAE files for the model0 and model1 arguments.

Once this new model is trained, you can also merge models into models: https://github.com/eyriewow/merge-models

Finally I was able to merge two checkpoints using this merge-models, Drop the two models in the same folder extracted and follow the steps, dont forget to write .ckpt in the name of the models

I'm not an expert with this, but I have been using this repo to merge models. Pretty basic process... choose two .ckpt files to combine, and specify the ratio you want to use. This is not any kind of concatenation, like an additive process where you can smush two models together without losing anything in the process. If you're looking for something like that, you'll want to look into proper fine-tuning, but that's a much more intensive process.

So, I found https://github.com/eyriewow/merge-models which merges models

According to my understanding dreambooth is a model, so using dreambooth to train stable diffusion is just combining/fusing these two models together? What' the difference between dreambooth x something vs github.com/eyriewow/merge-models ?