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Modify punctuation to full-width Chinese characters. #719

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Modify punctuation to full-width Chinese characters. #719

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4 changes: 2 additions & 2 deletions chapters/zh-CN/chapter1/3.mdx
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Expand Up @@ -30,7 +30,7 @@ Transformer 模型用于解决各种 NLP 任务，就像上一节中提到的那
## 使用pipelines [[使用pipelines]]

<iframe width="605" height="320" src="https://www.youtube.com/embed/tiZFewofSLM" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe>
(这里有一个视频，但是国内可能打不开,译者注)
（这里有一个视频，但是国内可能打不开，译者注）


🤗 Transformers 库中最基本的对象是 **pipeline()** 函数。它将模型与其必要的预处理和后处理步骤连接起来，使我们能够通过直接输入任何文本并获得最终的答案：
Expand Down Expand Up @@ -285,4 +285,4 @@ translator("Ce cours est produit par Hugging Face.")

</Tip>

到目前为止显示的pipeline主要用于演示目的。它们是为特定任务而编程的，不能对他们进行自定义的修改。在下一章中，您将了解 **pipeline()** 函数内部的内容以及如何进行自定义的修改。
到目前为止显示的pipeline主要用于演示目的。它们是为特定任务而编程的，不能对他们进行自定义的修改。在下一章中，您将了解 **pipeline()** 函数内部的内容以及如何进行自定义的修改。
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