waifu-diffusion VS stable-diffusion

It's slander to say that the WD team is milking donations in the same way UD is. They already have a public working model which they are continuing to train. The WD team has also implemented features like aspect ratio bucketing into their custom trainer. If they were really milking the project for donations they would have just used the base compvis trainer it was forked from.

Use one of the original SD repos, or the code for Waifu Diffusion, or the Smirkingface refactor.

My model is based off waifu-diffusion.

waifu diffusion (free) and NovelAI (paid afaik) is what I know

This is the one I use: https://github.com/harubaru/waifu-diffusion

This is called textual inversion which use many images and a small group of promtps to describe a single element, and there are two methods: with frozen model and with unfrozen model. The first one just creates a new “word” to “guide” the model, in other words, a word that means the same as a chunk of a prompt. The resulting data is a tiny file. The second one (better known dreamboth training) adds new data to de model, so it can copy the character’s characteristics and artist style more effecively resulting in a new model file (cpkt) There are not a single tutorial, so you can find many info on r/StableDiffusion. Also, there is a third method which is based on the original training (many images and its own description) Instruction are here: Training guide I don’t know if this guide is finished though

The model is a tweaked version of waifu-diffusion using textual inversion. Still not perfect but the AI can create pretty plausible images.

All of the generalized models and larger projects use model trainers that are offshoots of Latent Diffusion, which is what Stable Diffusion used. I recommend this one, but there are many others. Some support auto-captioning, captioning tools, or you can caption the images yourself.

Use one of the original SD repos, or the code for Waifu Diffusion, or the Smirkingface refactor.