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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This LORA is designed to address these issues. It only does one thing: making the image clearer without changing its content at all.
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Below is a comparison with Klein.
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Comparison with input
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Advanced version of High-resolution for Klein4B ( Released )
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## I'm an independent model and workflow developer. If you like my work and want to support independent development, please consider buying me a cup of coffee to keep this motivation going! Thank you very much.
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This LORA is designed to address these issues. It only does one thing: making the image clearer without changing its content at all.
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### Below is a comparison with Klein.
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### Comparison with input
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Advanced version of High-resolution for Klein4B ( Released )
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## I'm an independent model and workflow developer. If you like my work and want to support independent development, please consider buying me a cup of coffee to keep this motivation going! Thank you very much.
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[support](https://www.patreon.com/15597222/join) 🫡 May the AI-power be with you, see you soon !🫡
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