vqgan-clip-app VS ai-art-generator

If you want to try your hand at buggering your whole system - try playing with AI image generation as it uses all possible computer assets :D . There is a lot of forms and installations for those but I VQGANs from github the easiest. Problem is that some require familarity with shell, python and in some cases - you need to enable the Linux subsystem in Windows (is it called a subsystem? it is not exactly a VM). This one is the easiest to install out of all I tried. But I liked the results of Pixray most but I wrecked it. I use this one nowadays.

My attempt at centralizing models to be run locally looks like this: https://github.com/tnwei/vqgan-clip-app/, currently supports VQGAN-CLIP models and CLIP guided diffusion models.

I have a github project that will help you set up large batches of prompts too.

Hey all, just a note that I've updated my AI-art generator to work with Stable Diffusion (both txt2img and imgtoimg)! If you have a decent GPU (8GB VRAM+, though more is better), you should be able to use Stable Diffusion on your local computer.

I'm a software engineer, but a complete machine-learning noob (not exactly a linux guru, either). I'm trying to use the GPU for VQGAN+CLIP image generation. Running on an RTX 3060, I get almost 4 iterations per second, so a 512x512 image takes about 2 minutes to create with default settings. Running on the Tesla M40, I get about 0.4 iterations per second (~22 minutes per 512x512 image at the same settings). A full order of magnitude slower! I'd read that older Tesla GPUs are some of the top value picks when it comes to ML applications, but obviously with this level of performance that isn't the case at all. I figure I must be going wrong somewhere.