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title: README
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# Modular Diffusers Community 🧩
Creative generative workflows built with **Modular Diffusers** 🧨 for state-of-the-art open source models.
## What Modular Diffusers is
Diffusion pipelines are usually monolithic: one class per task, and a new task means a new pipeline. Modular
Diffusers breaks that into **composable blocks** — encode, prepare, denoise, decode — that you assemble into a
workflow, share components between them through a `ComponentsManager` so one loaded model serves several tasks,
and swap or subclass a single block instead of forking a pipeline. It is how a workflow that would be a graph of
custom nodes becomes a few lines of Python.
- 📚 [Documentation](https://huggingface.co/docs/diffusers/main/en/modular_diffusers/overview) · [Quickstart](https://huggingface.co/docs/diffusers/main/en/modular_diffusers/quickstart)
- 📝 [Introducing Modular Diffusers](https://huggingface.co/blog/modular-diffusers)
- 🧪 [Modular Diffusers on GitHub](https://github.com/huggingface/diffusers)
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