Dreambooth-Stable-Diffusion VS StableTuner

I did search online for an answer, but I am a PC noob, I didn't know what to do when I found this solution in this link: https://github.com/XavierXiao/Dreambooth-Stable-Diffusion/issues/113

Do you know some projects or guided tutorials that could help me? How many drawings with the desired style I should then have to give to train the AI model? I found Dreambooth on Stable Diffusion but it seams to be for another use case.

This seems to be an issue with the code and or the environment itself. There is an open bug for this where some suggestions are p provided by others on how to fix. https://github.com/XavierXiao/Dreambooth-Stable-Diffusion/issues/47

Could you provide some more detail on how this works? Did you just use this GitHub repository or did you put together your own implementation?

I think the best way to do this would be to train Dreambooth on a number of photos of Ray Liotta first, and use Stable Diffusion instead. https://github.com/XavierXiao/Dreambooth-Stable-Diffusion

Dreambooth. There are other ways, but that is the gold standard. It takes even more Vram than regular stable diffusion, so if you don't have a very beefy card (e.g. 4090 with 25 GB VRAM) various websites let you do it onlin for a small fee. You then download a new model that has all the old stuff (e.g.the 4 gigabyte SD 1.5 file) plus your new images. Like I said, there are other ways that are easier, but when people show great results they are usually talking about Dreambooth.

THE CODE (unofficial implementation, for the exact wording stating how little images you need read the paper) is designed with extremely little data in mind. I don't know how else to phrase it dude, do you think the training is a magic black box that runs with snail neurons? If you train a dreambooth model the jupyter ide makes calls to python files, those are the files. That is the code

Of all dreamboothing/finetuning implementations I tried I liked StableTuner the most. Might be worth giving it a shot to compare as well.

Largest I've gone is about 100 images for objects or people. I don't think it matters though, it can be a hassle setting up and resuming the training session each time if your doing small sessions. Stable Tuner can simplify all of this by helping you set everything up through their client installed locally. You can then easily do your training locally in short sessions or have it automatically packed up to be exported to colab or another gpu hosting service, also with the ability to train in short sessions. Its a smart way to manage large training projects like yours. It requires a bit of time setting up but most folks who have already played around with dreambooth should be able to navigate their way through easily enough. It has all the other training methods built into it too, including proper fine tuning https://github.com/devilismyfriend/StableTuner

Some people also like StableTuner: https://github.com/devilismyfriend/StableTuner

Stable Tuner seems like it's setup to allow training on regular/inpaint/depth models. https://github.com/devilismyfriend/StableTuner

StableTuner is an alternative to the sd_dreambooth plugin. It can do Dreambooth and Fine Tuning (I haven't tried this but I think it's embeddings) It uses diffusers but will convert between that and ckpt files, is for Windows/Nvidia, and uses a local app instead of a webapp. This is the only successful local Dreambooth I've done. You'll need to go to their discord for help but it's not hard to use.

Dreambooth is has better results in older commits. StableTuner is better for training : https://github.com/devilismyfriend/StableTuner