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Nunchaku Documentation
======================
**Nunchaku** is a high-performance inference engine optimized for low-bit diffusion models and LLMs,
as introduced in our paper `SVDQuant <paper_svdquant_>`_.
Check out `DeepCompressor <github_deepcompressor_>`_ for the quantization library.
.. toctree::
:maxdepth: 2
:caption: Installation
installation/installation.rst
installation/setup_windows.rst
.. toctree::
:maxdepth: 1
:caption: Usage Tutorials
usage/basic_usage.rst
usage/qwen-image.rst
usage/qwen-image-edit.rst
usage/lora.rst
usage/kontext.rst
usage/sdxl.rst
usage/controlnet.rst
usage/qencoder.rst
usage/offload.rst
usage/attention.rst
usage/cache.rst
usage/pulid.rst
usage/ip_adapter.rst
usage/zimage.rst
.. toctree::
:maxdepth: 1
:caption: Python API Reference
python_api/nunchaku.rst
.. toctree::
:maxdepth: 1
:caption: Useful Tools
:titlesonly:
ComfyUI Plugin: ComfyUI-nunchaku <https://nunchaku.tech/docs/ComfyUI-nunchaku/>
Custom Model Quantization: DeepCompressor <https://github.com/nunchaku-tech/deepcompressor>
Gradio Demos <https://github.com/nunchaku-tech/nunchaku/tree/main/app>
.. toctree::
:maxdepth: 1
:caption: Other Resources
faq/faq.rst
developer/contribution_guide.rst
developer/docstring.rst
developer/build_docs.rst

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