textual_inversion VS stable-diffusion-webui

Checking out https://github.com/rinongal/textual_inversion, which has some possibly informative examples and scripts.

I think currently you will need about 20GB VRam..., options are: 1. https://github.com/rinongal/textual_inversion - localy

Rinongal and nicolai256 versions, the latter of which is also the one explained in Nerdy Rodent's youtube video https://www.youtube.com/watch?v=WsDykBTjo20, work but they also have an issue of lacking editability in comparison to one made by huggingface's collab which is followed up in a very long issue on Rinongal's Github. You can add accumulate_grad_batches: 4 to the end of the finetune files like shown in Nerdy Rodent's video at this time stamp to try to alleviate this issue, but the quality isn't as good as one made in the online collab.

That may mostly solve that but it’s too early right now: https://github.com/rinongal/textual_inversion

For fun I tried to make an entire animated music video but it took over one week of processing and basically fell apart coherently by 30 seconds so just did one third:

https://youtu.be/f3GfUKJBUYA

The huggingface models don't work with the local stable diffusion, only the models trained locally with this repo https://github.com/rinongal/textual_inversion can be installed, at least for now.

* LLaVA model: I'll add more documentation. You are right Llava could not generate images. For image generation I don't have immediate plans, but checkout these projects for local image generation.

- https://diffusionbee.com/

- https://github.com/comfyanonymous/ComfyUI

- https://github.com/AUTOMATIC1111/stable-diffusion-webui

I would love to be able to have a native stable diffusion experience, my rx 580 takes 30s to generate a single image. But it does work after following https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki...

I got this up and running on my windows machine in short order and I don't even know what stable diffusion is.

But again, it would be nice to have first class support to locally participate in the fun.

In Auto1111, that just uses Image.blend. :)

https://github.com/AUTOMATIC1111/stable-diffusion-webui/blob...

I used SDXL in automatic1111 webui for both images. Now that I think about it, the procedure I described was how I made this one, but the one that looks like an illustration was done in two steps. I used the canny ControlNet as I said for the outer part of the logo to preserve the shape of the fonts, but I had to turn it off for the boot to give SDXL leeway to add detail and make it look more like a boot.

That said, please do learn coding and don't get discouraged when somebody says to learn PyTorch or recommends using a Jupiter notebook with no further information on how to translate the skill into images. I would highly recommend some short term goals. Get your feet wet by taking apart the UIs. The comfy API documentation is here and the A1111 API documentation is here. There is a difference in completeness, welcome to programming. Writing nodes or plugins is also a good way to jump into this world. Custom wildcard logic might be very attractive to you if you aren't the type that want to deal with a nested file structure to simulate logic.

Possibly Unprompted? https://github.com/AUTOMATIC1111/stable-diffusion-webui/discussions/8094

version: v1.6.1  •  python: 3.10.13  •  torch: 2.0.1+cu118  •  xformers: 0.0.20  •  gradio: 3.41.2  •  checkpoint: 6e8d4871f8