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| title: README | |
| emoji: 🧩 | |
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| colorTo: pink | |
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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) | |