AyyMD Stable Diffuse v1.4 for Wangblows 10 (by anon)

When you want it to run on GNU\Linux, follow the ROCm guide. (https://rentry.org/sdamd)


You have installed Python 3.x (min. 3.7)


A huggingface.co account (to generate and download the stable-diffusion v1.4 model)


Accepted terms of use for stable diffusion with your account (download will fail without it)



  • Make a folder where you will download all stuff into
  • Open Command Line (as Administrator, or it will fail later on because of symlinks)
  • Clone special hack version by harishanand95
    git clone https://github.com/harishanand95/diffusers.git
    cd diffusers && git checkout dml && pip install -e .
    pip install transformers ftfy scipy
  • Check for the newest nightly of onnx and download it (at time of writing it was "1.13.0.dev20220901005")

If you are on Python 3.7 download the file that ends with **-cp37-cp37m-win_amd64.whl
If you are on Python 3.8 download the file that ends with **-cp38-cp38-win_amd64.whl
If you are on Python 3.9 download the file that ends with **-cp39-cp39-win_amd64.whl
If you are on Python 3.10 download the file that ends with **-cp310-cp310-win_amd64.whl

  • I still use Python 3.7 so for me it is:
  • Download it and install it
    pip install ort_nightly_directml-1.13.0.dev20220901005-cp37-cp37m-win_amd64.whl

An error message like this "ERROR: ort_nightly_directml-1.13.0.dev20220830001-cp38-cp38-win_amd64.whl is not a supported wheel on this platform." means that there is mismatch in python version and the downloaded package supported python version.

Generating a onnx-based stable-diffusion v1.4 model

  • Go to folder "diffusers\examples\inference"
  • Login via cli and generate a token (huggingface-cli was installed by transformers package)
    huggingface-cli login
  • Start downloading and generating of stable-diffusion v1.4 model
    python ./save_onnx.py

Generate a image

  • Open dml_onnx.py with notepad and edit what you want to generate at the bottom of the file in "prompt" variable
  • Default for testing is: prompt = "a photo of an astronaut riding a horse on mars"
  • Save and execute with "python ./dml_onnx.py"
  • After a bit of time you will get a png in the "diffusers\examples\inference" folder.

I have about ~3.30/it on my good ol AMD RX 480 and a image takes about "2:30 min". You should have a higher number.

Pub: 02 Sep 2022 16:24 UTC
Views: 74321