UPDATE: A faster (20x) approach for running Stable Diffusion using MLIR/Vulkan/IREE is available on Windows:
conda create --name sd39 python=3.9 -y
conda activate sd39
pip install diffusers==0.3.0
pip install transformers
pip install onnxruntime
pip install onnx
You can download the nightly onnxruntime-directml release from the link below
Run python --version
to find out, which whl file to download.
- If you are on Python3.7, download the file that ends with **-cp37-cp37m-win_amd64.whl.
- If you are on Python3.8, download the file that ends with **-cp38-cp38m-win_amd64.whl
- and likewise
pip install ort_nightly_directml-1.13.0.dev20220908001-cp39-cp39-win_amd64.whl --force-reinstall
This apporach is faster than downloading the onnx models files.
- Download diffusers/scripts/convert_stable_diffusion_checkpoint_to_onnx.py to your working directory. You can try the command below to download the script.
wget https://raw.githubusercontent.com/huggingface/diffusers/main/scripts/convert_stable_diffusion_checkpoint_to_onnx.py
- Run
huggingface-cli.exe login
and provide huggingface access token. - Convert the model using the command below. Models are stored in
stable_diffusion_onnx
folder.
python convert_stable_diffusion_checkpoint_to_onnx.py --model_path="CompVis/stable-diffusion-v1-4" --output_path="./stable_diffusion_onnx"
Here is an example python code for stable diffusion pipeline using huggingface diffusers.
from diffusers import StableDiffusionOnnxPipeline
pipe = StableDiffusionOnnxPipeline.from_pretrained("./stable_diffusion_onnx", provider="DmlExecutionProvider")
prompt = "a photo of an astronaut riding a horse on mars"
image = pipe(prompt).images[0]
image.save("astronaut_rides_horse.png")
Hey Harisha, Thanks for your answer,
I have to create a TOKEN diffrent from the first one right? (I still have your first method method runing in the background),
Anyway hardcoded my new token into the "True" value but it did nothing.
Tried both tokens! This time it's different. It's as if I can't even write anything in the miniconda window, and I press enter it says wrong token even if I try to hardcode a token into my convert_stable_diffusion_checkpoint_to_onnx.py file.