Instructions to use peter-sushko/RealEdit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use peter-sushko/RealEdit 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("peter-sushko/RealEdit", 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
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# REALEDIT: Reddit Edits As a Large-scale Empirical Dataset for Image Transformations
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Project page: https://peter-sushko.github.io/RealEdit/
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Data: https://huggingface.co/datasets/peter-sushko/RealEdit
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Paper: https://arxiv.org/pdf/2502.03629
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<img src="https://peter-sushko.github.io/RealEdit/static/images/teaser.svg"/>
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# REALEDIT: Reddit Edits As a Large-scale Empirical Dataset for Image Transformations
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Project page: https://peter-sushko.github.io/RealEdit/
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Data: https://huggingface.co/datasets/peter-sushko/RealEdit
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Paper: https://arxiv.org/pdf/2502.03629
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<img src="https://peter-sushko.github.io/RealEdit/static/images/teaser.svg"/>
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