Stable Diffusion (DALLE-2 clone) on AMD GPU

Get Stable Diffusion running on your AMD GPU without needing CUDA.
Note: Tested on Radeon RX68XX and 69XX series GPU's with Ubuntu 20.04/22.04 and ArchLinux. User reports indicate this method is working on several other GPU's including Radeon VII, Vega 56/64, 6700(XT), 6600(XT) [with env workaround], and even 5700(XT) series (see below for additional step).

Should theoretically work on RX470/480/570/580 GPU's with at least 8GB of ram too. You can check whether your AMD GPU supports ROCm here: https://community.amd.com/t5/knowledge-base/amd-rocm-hardware-and-software-support-document/ta-p/489937

ENV Workaround for 66XX(XT) and some 67XX(XT) GPU's:
https://github.com/RadeonOpenCompute/ROCm/issues/1756#issuecomment-1160386571

Update: This method also works on the 56XX/57XX(XT) series, but requires an additional step:
https://www.reddit.com/r/StableDiffusion/comments/ww436j/comment/imp7bx2/

RX 470/480/570/580/590 Users: 8GB RAM required. The bundled PyTorch has dropped support for these older cards, you will have to follow my video instructions, but use a different pytorch binary that includes support linked here: https://www.reddit.com/r/StableDiffusion/comments/ww436j/comment/ipkfm35/

STEP 1: Prepare ROCm Kernel Drivers
a) ArchLinux - AUR - See Video
b) Ubuntu - See video - https://github.com/RadeonOpenCompute/ROCm-docker/blob/master/quick-start.md

STEP 2: Download Docker Image & Setup Container
https://hub.docker.com/r/rocm/pytorch

STEP 3: Clone GIT repo
https://github.com/CompVis/stable-diffusion

STEP 4: Download Public Model Weights (v1.4)
https://huggingface.co/CompVis/stable-diffusion-v-1-4-original

Step 5: Setup Conda Environment
https://pytorch.org/

00:00-00:20 Introduction
00:21-01:05 Demo
01:06-02:30 1-Prepare Kernel Drivers
02:31-04:12 2-Docker Image
04:13-04:56 3-Clone Repository
04:57-05:31 4-Download Weights
05:32-10:51 5-Conda Environment

#stablediffusion #stable-diffusion #amd