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
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### Comparison with input
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Advanced version of High-resolution for Klein4B (
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Advanced version of High-resolution for Klein9B (
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Whether it's photos, film, animation, stylized illustrations, or digital art, all can be enhanced to high definition with a single click. If you want to build your own workflow, it is recommended to use it in conjunction with the upscale model for better results.
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### Comparison with input
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Advanced version of High-resolution for Klein4B ( ✔️ )
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Advanced version of High-resolution for Klein9B ( ✔️ )
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Whether it's photos, film, animation, stylized illustrations, or digital art, all can be enhanced to high definition with a single click. If you want to build your own workflow, it is recommended to use it in conjunction with the upscale model for better results.
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