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Merge pull request #3959 from Evezerest/2.3

Update models.md
# PP-OCR模型与配置文件 # PP-OCR模型
PP-OCR模型与配置文件一章主要补充一些OCR模型的基本概念、配置文件的内容与作用以便对模型后续的参数调整和训练中拥有更好的体验。 PP-OCR模型一章主要补充一些OCR模型的基本概念、配置文件的内容与作用以便对模型后续的参数调整和训练中拥有更好的体验。
本章包含三个部分,首先在[PP-OCR模型下载](./models_list.md)中解释PP-OCR模型的类型概念,并提供所有模型的下载链接。然后在[配置文件内容与生成](./config.md)中详细说明调整PP-OCR模型所需的参数。最后的[模型库快速使用](./inference_ppocr.md)是对第一节PP-OCR模型库使用方法的介绍,可以通过Python推理引擎快速利用丰富的模型库模型获得测试结果。 本章包含两个部分,首先在[PP-OCR模型下载](./models_list.md)中解释PP-OCR模型的类型概念,并提供所有模型的下载链接。[模型库快速使用](./inference_ppocr.md)是对PP-OCR模型库使用方法的介绍,可以通过Python推理引擎快速利用丰富的模型库模型获得测试结果。
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# PP-OCR Model and Configuration # PP-OCR Model and Configuration
The chapter on PP-OCR model and configuration file mainly adds some basic concepts of OCR model and the content and role of configuration file to have a better experience in the subsequent parameter adjustment and training of the model. The chapter on PP-OCR model and configuration file mainly adds some basic concepts of OCR model and the content and role of configuration file to have a better experience in the subsequent parameter adjustment and training of the model.
This chapter contains three parts. Firstly, [PP-OCR Model Download](. /models_list_en.md) explains the concept of PP-OCR model types and provides links to download all models. Then in [Yml Configuration](. /config_en.md) details the parameters needed to fine-tune the PP-OCR models. The final [Python Inference for PP-OCR Model Library](. /inference_ppocr_en.md) is an introduction to the use of the PP-OCR model library in the first section, which can quickly utilize the rich model library models to obtain test results through the Python inference engine. This chapter contains two parts. Firstly, [PP-OCR Model Download](. /models_list_en.md) explains the concept of PP-OCR model types and provides links to download all models. The next [Python Inference for PP-OCR Model Library](. /inference_ppocr_en.md) is an introduction to the use of the PP-OCR model library, which can quickly utilize the rich model library models to obtain test results through the Python inference engine.
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