Instructions to use benjamin-paine/stable-diffusion-v1-5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use benjamin-paine/stable-diffusion-v1-5 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("benjamin-paine/stable-diffusion-v1-5", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
SHA256 checksums FYI
Hi benjamin-paine,
Thank you for kindly sharing the weights with the community!
I happen to have most (not all, unfortunately) of original latest weights commited on Aug 23 cached and have uploaded them in hf repo KiwiXR/stable-diffusion-v1-5. I also attached their sha256sum in https://huggingface.co/KiwiXR/stable-diffusion-v1-5/blob/main/sha256.lst if you are interested.
By the way, you might want to find the sha256 provided by git lfs by clicking on the model files, and compare them to those on wayback machine: https://web.archive.org/web/20231227043125/https://huggingface.co/runwayml/stable-diffusion-v1-5
Best regards.
Ah brilliant, thank you for the list! I was able to verify the integrity of these files - and I hadn't thought that the wayback machine would cache the pages that displayed the checksums but they were indeed cached, and I was able to verify for the inpainting repository as well, so thanks for that idea, too.