Dreambooth-Stable-Diffusion VS diffusers

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

ShivamShrirao's Diffusers Pretrained diffusion models across multiple modalities.

Like the title say I'm trying to fine-tune a model to match a style of a popular manhwa. I'm using the ShivamShrirao Google Colab to accomplish this.

I am running the DreamBooth_Stable_Diffusion.ipynb notebook from ShivamShrirao locally on my machine. Let's say I have trained for 500 iterations and it hasn't converged yet. How do I make it resume training from that iteration so it can do another 500?

My understanding, based on messages from an (alleged) representative of colabs, is that the webui is the problem, not SD itself. This also seems to be the consensus in the comments section of other posts. I have not yet seen a link to colab based webui alternatives so here is something I found from a tutorial. I am certain that there are better alternatives. Anyone have a better idea? This will still probably be useful to other people like me who are just messing around.

I'm running ShivamShrirao's fork of diffusers; ran into a fp16 issue and had to patch in a fix from the main branch ( #1567 ).

I am running Shivam Stable Diffusion Jupyter notebook: diffusers/DreamBooth_Stable_Diffusion.ipynb at main · ShivamShrirao/diffusers · GitHub.

Are you using this one? https://github.com/S