Unverified Commit c98c157a authored by Álvaro Somoza's avatar Álvaro Somoza Committed by GitHub
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[Docs] Add Z-Image docs (#12775)



* initial

* toctree

* fix

* apply review and fix

* Update docs/source/en/api/pipelines/z_image.md
Co-authored-by: default avatarSteven Liu <59462357+stevhliu@users.noreply.github.com>

* Update docs/source/en/api/pipelines/z_image.md
Co-authored-by: default avatarSteven Liu <59462357+stevhliu@users.noreply.github.com>

* Update docs/source/en/api/pipelines/z_image.md
Co-authored-by: default avatarSteven Liu <59462357+stevhliu@users.noreply.github.com>

---------
Co-authored-by: default avatarSteven Liu <59462357+stevhliu@users.noreply.github.com>
parent f12d161d
......@@ -401,6 +401,8 @@
title: WanAnimateTransformer3DModel
- local: api/models/wan_transformer_3d
title: WanTransformer3DModel
- local: api/models/z_image_transformer2d
title: ZImageTransformer2DModel
title: Transformers
- sections:
- local: api/models/stable_cascade_unet
......@@ -646,6 +648,8 @@
title: VisualCloze
- local: api/pipelines/wuerstchen
title: Wuerstchen
- local: api/pipelines/z_image
title: Z-Image
title: Image
- sections:
- local: api/pipelines/allegro
......
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# ZImageTransformer2DModel
A Transformer model for image-like data from [Z-Image](https://huggingface.co/Tongyi-MAI/Z-Image-Turbo).
## ZImageTransformer2DModel
[[autodoc]] ZImageTransformer2DModel
\ No newline at end of file
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Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at
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# Z-Image
<div class="flex flex-wrap space-x-1">
<img alt="LoRA" src="https://img.shields.io/badge/LoRA-d8b4fe?style=flat"/>
</div>
[Z-Image](https://huggingface.co/papers/2511.22699) is a powerful and highly efficient image generation model with 6B parameters. Currently there's only one model with two more to be released:
|Model|Hugging Face|
|---|---|
|Z-Image-Turbo|https://huggingface.co/Tongyi-MAI/Z-Image-Turbo|
## Z-Image-Turbo
Z-Image-Turbo is a distilled version of Z-Image that matches or exceeds leading competitors with only 8 NFEs (Number of Function Evaluations). It offers sub-second inference latency on enterprise-grade H800 GPUs and fits comfortably within 16G VRAM consumer devices. It excels in photorealistic image generation, bilingual text rendering (English & Chinese), and robust instruction adherence.
## ZImagePipeline
[[autodoc]] ZImagePipeline
- all
- __call__
\ No newline at end of file
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