Image-to-Image
Diffusers
Safetensors
MageFlowPipeline
image-editing
instruction-based-editing
diffusion
rectified-flow
mage-flow
Instructions to use microsoft/Mage-Flow-Edit-Turbo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use microsoft/Mage-Flow-Edit-Turbo 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("microsoft/Mage-Flow-Edit-Turbo", torch_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
README: update citation to arXiv article entry
Browse files
README.md
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@@ -374,11 +374,10 @@ A web UI with **Text → Image** and **Image Edit** tabs; models load lazily on
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## 📝 Citation
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```bibtex
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@
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title
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author
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url = {https://github.com/microsoft/Mage}
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}
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```
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## 📝 Citation
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```bibtex
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@article{zhang2026mageflow,
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title={Mage-Flow: An Efficient Native-Resolution Foundation Model for Image Generation and Editing},
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author={Zhang, Xinjie and Zhang, Peng and Zheng, Shicheng and Guo, Jinghao and Jia, Zhaoyang and Shen, Yifei and Guo, Xun and Luo, Yuxuan and Li, Jiahao and Xie, Wenxuan and Pu, Fanyi and Zhang, Xiaoyi and Zhang, Kaichen and Guo, Zongyu and Bi, Tianci and Gui, Dongnan and Liu, Zhening and Wen, Zimo and Zheng, Zihan and Yang, Senqiao and Li, Xiao and Wang, Jinglu and Li, Bin and Lu, Yan},
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journal={arXiv preprint},
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year={2026}
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}
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```
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