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:
- a9df284358a102650e0e43409e8f0e96c03c2ebf63f285fb39a4372339a9560b
- Size of remote file:
- 5.33 MB
- SHA256:
- 06fd78ba8b576a2b2b4c96ec2011532d697ad6a6a259bba5d7ef6a699359125a
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