Instructions to use inclusionAI/TwinFlow with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use inclusionAI/TwinFlow with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("inclusionAI/TwinFlow", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Update README.md
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README.md
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[](https://zhenglin-cheng.com/twinflow) 
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[](https://huggingface.co/inclusionAI/TwinFlow) 
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[](https://github.com/inclusionAI/TwinFlow) 
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<a href="https://arxiv.org/abs/2512.05150" target="_blank"><img src="https://img.shields.io/badge/Paper-b5212f.svg?logo=arxiv" height="21px"></a>
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## News
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- We release **TwinFlow-Qwen-Image-v1.0**! And we are also working on **Z-Image-Turbo to make it more faster**!
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## TwinFlow
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[](https://zhenglin-cheng.com/twinflow) 
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[](https://huggingface.co/inclusionAI/TwinFlow) 
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[](https://huggingface.co/inclusionAI/TwinFlow-Z-Image-Turbo) 
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[](https://github.com/inclusionAI/TwinFlow) 
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<a href="https://arxiv.org/abs/2512.05150" target="_blank"><img src="https://img.shields.io/badge/Paper-b5212f.svg?logo=arxiv" height="21px"></a>
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## News
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- We release experimental version of faster Z-Image-Turbo!
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- We release **TwinFlow-Qwen-Image-v1.0**! And we are also working on **Z-Image-Turbo to make it more faster**!
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## TwinFlow
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