Instructions to use codeShare/unstableRevolution_SDNQ with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use codeShare/unstableRevolution_SDNQ with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline from diffusers.utils import load_image # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("codeShare/unstableRevolution_SDNQ", dtype=torch.bfloat16, device_map="cuda") prompt = "Turn this cat into a dog" input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png") image = pipe(image=input_image, prompt=prompt).images[0] - Notebooks
- Google Colab
- Kaggle
File size: 215 Bytes
1a6dca8 | 1 2 3 4 | This folder holds unquantized checkpoints SDNQ can only be saved in diffusers format (the stuff with folders in the repo) These checkpoints serve as easy access fallbacks should one wish to do other quantizations. |