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add dygraph link in readme (PaddlePaddle#560)
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README.md

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@@ -228,6 +228,9 @@ pip install paddleslim==1.2.0 -i https://pypi.tuna.tsinghua.edu.cn/simple
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## 使用
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- [快速开始](docs/zh_cn/quick_start):通过简单示例介绍如何快速使用PaddleSlim。
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- 动态图:
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- 剪枝:[教程](dygraph_docs/)[示例](demo/dygraph/pruning)
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- 量化:[示例](demo/dygraph/quant)
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- [进阶教程](docs/zh_cn/tutorials):PaddleSlim高阶教程。
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- [模型库](docs/zh_cn/model_zoo.md):各个压缩策略在图像分类、目标检测和图像语义分割模型上的实验结论,包括模型精度、预测速度和可供下载的预训练模型。
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- [API文档](https://paddlepaddle.github.io/PaddleSlim/api_cn/index.html)

README_en.md

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## Usage
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- [QuickStart](https://paddlepaddle.github.io/PaddleSlim/quick_start/index_en.html): Introduce how to use PaddleSlim by simple examples.
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- Dynamic graph
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- Pruning: [Tutorial](dygraph_docs/), [Demo](demo/dygraph/pruning)
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- Quantization: [Demo](demo/dygraph/quant)
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- [Advanced Tutorials](https://paddlepaddle.github.io/PaddleSlim/tutorials/index_en.html):Tutorials about advanced usage of PaddleSlim.
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- [Model Zoo](https://paddlepaddle.github.io/PaddleSlim/model_zoo_en.html):Benchmark and pretrained models.
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- [API Documents](https://paddlepaddle.github.io/PaddleSlim/api_en/index_en.html)
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- [Algorithm Background](https://paddlepaddle.github.io/PaddleSlim/algo/algo.html): Introduce the background of quantization, pruning, distillation, NAS.
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- [PaddleDetection](https://github.com/PaddlePaddle/PaddleDetection/tree/master/slim): Introduce how to use PaddleSlim in PaddleDetection library.
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- [PaddleSeg](https://github.com/PaddlePaddle/PaddleSeg/tree/develop/slim): Introduce how to use PaddleSlim in PaddleSeg library.
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- [PaddleLite](https://paddlepaddle.github.io/Paddle-Lite/): How to use PaddleLite to deploy models generated by PaddleSlim.
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- [TensorRT Deploy](demo/quant/deploy/TensorRT): How to use TensorRT to deploy models generated by PaddleSlim.
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## Performance

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