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Try to passs CI check
Signed-off-by: SamYuan1990 <[email protected]>
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docs/source/zh/_toctree.yml

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- sections:
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- local: index
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title: 🧨 Diffusers
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title: Diffusers
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- local: quicktour
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title: 快速入门
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- local: stable_diffusion
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- local: installation
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title: 安装
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title: 开始
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- title: Training
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isExpanded: false
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sections:
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- local: training/overview
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title: Overview
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- local: training/adapt_a_model
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title: Adapt a model to a new task
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- title: Models
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sections:
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- local: training/text2image
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title: Text-to-image
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- local: training/controlnet
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title: ControlNet
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- title: Methods
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sections:
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- local: training/text_inversion
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title: Textual Inversion
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- local: training/dreambooth
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title: DreamBooth
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- local: training/lora
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title: LoRA
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- title: Inference optimization
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isExpanded: false
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sections:
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- local: optimization/fp16
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title: Accelerate inference
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- title: Community optimizations
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sections:
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- local: optimization/xformers
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title: xFormers
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- title: Model accelerators and hardware
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isExpanded: false
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sections:
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- local: using-diffusers/stable_diffusion_jax_how_to
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title: JAX/Flax
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- local: optimization/onnx
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title: ONNX
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- title: DiffusionPipeline
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isExpanded: false
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sections:
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- local: using-diffusers/schedulers
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title: Load schedulers and models
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- title: Resources
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isExpanded: false
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sections:
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- local: conceptual/philosophy
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title: Philosophy
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- local: conceptual/contribution
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title: How to contribute?
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- local: conceptual/ethical_guidelines
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title: Diffusers' Ethical Guidelines
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- local: conceptual/evaluation
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title: Evaluating Diffusion Models

docs/source/zh/conceptual/contribution.md

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### 风格指南
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对于文档字符串,🧨 Diffusers 遵循 [Google 风格指南](https://google.github.io/styleguide/pyguide.html)。
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Disclaimers: This content is powered by i18n-agent-action with LLM service https://api.deepseek.com with model deepseek-chat, for some reason, (for example, we are not native speaker) we use LLM to provide this translate for you. If you find any corrections, please file an issue or raise a PR back to github, and switch back to default language.

docs/source/zh/training/adapt_a_model.md

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```
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此时文生图模型的其他组件权重仍保持预训练状态,但UNet的输入卷积层权重(`conv_in.weight`)会随机初始化。由于这一关键变化,必须对模型进行修复任务的微调,否则模型将仅会输出噪声。
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Disclaimers: This content is powered by i18n-agent-action with LLM service https://api.deepseek.com with model deepseek-chat, for some reason, (for example, we are not native speaker) we use LLM to provide this translate for you. If you find any corrections, please file an issue or raise a PR back to github, and switch back to default language.

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