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[Docs] Add Z-Image docs (#12775)

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* initial

* toctree

* fix

* apply review and fix

* Update docs/source/en/api/pipelines/z_image.md

Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

* Update docs/source/en/api/pipelines/z_image.md

Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

* Update docs/source/en/api/pipelines/z_image.md

Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

---------

Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
This commit is contained in:
Álvaro Somoza
2025-12-05 11:05:47 -03:00
committed by GitHub
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commit c98c157a9e
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docs/source/en/_toctree.yml
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@@ -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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<!--Copyright 2025 The HuggingFace Team. All rights reserved.
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
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on
an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the
specific language governing permissions and limitations under the License.
-->
# ZImageTransformer2DModel
A Transformer model for image-like data from [Z-Image](https://huggingface.co/Tongyi-MAI/Z-Image-Turbo).
## ZImageTransformer2DModel
[[autodoc]] ZImageTransformer2DModel

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<!--Copyright 2025 The HuggingFace Team. All rights reserved.
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
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on
an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the
specific language governing permissions and limitations under the License.
-->
# 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__