Instructions to use NO8D/HighResolution with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use NO8D/HighResolution 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("NO8D/HighResolution", dtype=torch.bfloat16, device_map="cuda") prompt = "High Resolution" 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
- Xet hash:
- 6343d9ebd7fe2f76d5a7f3415d9b8df295f2df3642eb11246f8e58920d33e10c
- Size of remote file:
- 82.9 MB
- SHA256:
- d280c26417966302baa39440bc23ec007ee2d1561c9bd5440d42d73e9383362b
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