- Joined
- Dec 19, 2022
Sure thing!Would you be willing to give me a few pointers to get me started on SD with an AMD card?
So basically get docker set up on your computer, pull the rocm-pytorch image, and start it. Inside the container you git clone the automatic1111 repo and do the normal setup (same as for Nvidia). The SD general on /g/ has a long list of models you can download, but I'd stick with SD 1.4 and 1.5 unless you specifically want anime-style, in which case I'd do a 70% blend of SD with one or more models trained on anime (avoid the danbooru-only models, it's impossible to make them not be lewd). Launch SD and read the end of the terminal output to get the port (or specify a port when you launch it). In a web browser go to 127.0.0.1:port. Go into the settings and tell it to save outputs to /outputs. Close SD by hitting ctrl-c in the terminal. Open a new terminal, and save a snapshot of your rocm-pytorch container as "stablediffusion". Now you can close down your open container. Write a bash script to start the docker daemon, save its PID into a variable, and then launch your docker container. Include an argument to bind mount /outputs in the container to a folder on your computer. The next line should be kill "$PID" to stop the daemon, and then chown -Rv you:users "/absolute path to your outputs folder" to automatically own your output files. One of the benefits of using docker is that if something breaks with an update, which happens every now and then, you can very easily roll back to a working install. Just don't release old snapshots until you're sure the updated one works well. Personally, I don't delete them at all. I could roll back all the way to September 2022, when I first played with SD, if I wanted.
Just ask me if you need more specifics, okay? We could maybe do it with PMs or if you want to start a new thread instead, since it's kind of offtopic for this thread.
That sounds like what you were actually running was the CPU version? Yeah, performance on that is going to be beyond awful. My 6900XT gets about 8it/s, which is decent, though still quite a bit lower than an Nvidia would do. Oh well. Your RDNA3 card will be much faster. You'll be able to do higher than 768x768 too, that's about where the limit for my card is.I have tried. I found a tutorial which was supposed to "convert" models somehow. I don't recall it involving Docker at all. And whilst I sort of got it working the results were greatly disappointing and I then broke it with some sort of version issue.
I'm not a technical novice, but I don't really know how to get this working and just a few good links or the concepts would help. The tutorial I read didn't really explain everything and assumed you understood how SD and models all work. So when something went wrong, I couldn't figure it out.