stable-diffusion-aesthetic-gradients VS kohya-trainer

You might want to try https://github.com/vicgalle/stable-diffusion-aesthetic-gradients to see if you can reproduce the style without necessarily having to come up with text descriptions

Aesthetic gradients plugin for Automatic1111 WebUI

I think you're describing Aesthetic Gradients

Its different imo. Look at the floral example flower_plant https://github.com/vicgalle/stable-diffusion-aesthetic-gradients

Also, since you have found some interesting aesthetic embeddings, if you wish, you can contribute your embeddings by opening a PR in the repo https://github.com/vicgalle/stable-diffusion-aesthetic-gradients !

We could definitely use some help with generating aesthetic gradient tensors if you think you'd like to take some of that on. It's a fairly straightforward process and it's all laid out in this repo. I would love to see what you come up with and how you implement it. The file output is a pytorch tensor so it's extremely small which makes it great for sharing with friends!

You could look into generating your own aesthetic gradients using a dataset of people from a distance with faces you like in the style you're going for. Here's the repo. It's much more compute efficient than retraining over and over to adjust for overtraining with many tokens at a time. Although it can take some time adjusting your aesthetic steps. You should be able to get results! Just explore and have fun!

This longer colab notebook: I did use this one (or one of the slight derivatives of it) and got out a safetensors file, but the lora didn't work at all--I'd use it a increase it's weight but I just would see no effect

It isn't what you are asking for (sry) but I struggled with this thing for way too long until I found out about the Kohya Trainer. https://github.com/Linaqruf/kohya-trainer So much easier with a lot of videos by the various YT folks. Standalone WebUI that just works. Life is good here!

It's seem that he is stable diffusion model creators. In that space, it's less knowing about the code and more experimenting on what would happen in the training. The stable diffusion community has repertoire of fine-tuning tools that is accessible for someone who have no single idea on the code behind it, no different than using application like kohya.

Have you tried out one of the colabs from https://github.com/Linaqruf/kohya-trainer ? The colabs themselves are pretty long, but you just have to read each step and then usually push the button to run that cell, then move on to the next one.

** https: //github.com/linaqruf/kohya-trainer**

There are a lot of variables that affect what kind of settings to use, but afaik the best solution to finding the right step count for what your training is still just to save multiple epochs and then run a x/y/z plot comparison. If you can't do that locally because of your 4gb card, you could try using Lora colabs that include inference capabilities.

You seem to be a little confused. You wont find an ipynb of a model. You would reference a model via a content portal like hugginface. If your model is hosted there, you dont have to download it to your computer or gdrive first. You just reference it with the hugginface-style reference, ie runwayml/stable-diffusion-v1-5. Some colabs will let you also reference a URL to pull down the model. Example. https://github.com/Linaqruf/kohya-trainer/blob/main/kohya-LoRA-dreambooth.ipynb. In that case, you can get the direct url to a checkpoint, for example at civit.ai. If you're decent at messing around with code, you can deconstruct that code block to use in a different colab. As for gdrive, it's only a couple dollars to get 100G.

Try this colab to train Lora, it can generate image without the UI too