fix doc for whl (#552)
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PaddleClas is a toolset for image classification tasks prepared for the industry and academia. It helps users train better computer vision models and apply them in real scenarios.
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**Recent update**
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- 2021.01.08 Add support for whl package and its usage, Model inference can be done by simply install paddleclas using pip.
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- 2020.12.16 Add support for TensorRT when using cpp inference to obain more obvious acceleration.
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- 2020.12.06 Add `SE_HRNet_W64_C_ssld` pretrained model, whose Top-1 Acc on ImageNet-1k dataset reaches 84.75%.
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- 2020.11.23 Add `GhostNet_x1_3_ssld` pretrained model, whose Top-1 Acc on ImageNet-1k dataset reaches 79.38%.
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- 2020.10.12 Add Paddle-Lite demo。
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- 2020.10.10 Add cpp inference demo and improve FAQ tutorial.
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- 2020.09.17 Add `HRNet_W48_C_ssld` pretrained model, whose Top-1 Acc on ImageNet-1k dataset reaches 83.62%. Add `ResNet34_vd_ssld` pretrained model, whose Top-1 Acc on ImageNet-1k dataset reaches 79.72%.
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- 2020.09.07 Add `HRNet_W18_C_ssld` pretrained model, whose Top-1 Acc on ImageNet-1k dataset reaches 81.16%.
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- [more](./docs/en/update_history_en.md)
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@ -79,6 +79,7 @@ PaddleClas is a toolset for image classification tasks prepared for the industry
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- [C++ inference](./deploy/cpp_infer/readme_en.md)
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- [Serving deployment](./deploy/hubserving/readme_en.md)
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- [Mobile](./deploy/lite/readme_en.md)
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- [Inference using whl ](./docs/en/whl_en.md)
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- [Model Quantization and Compression](docs/en/extension/paddle_quantization_en.md)
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- Advanced tutorials
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- [Knowledge distillation](./docs/en/advanced_tutorials/distillation/distillation_en.md)
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**近期更新**
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- 2021.01.08 添加whl包及其使用说明,直接安装paddleclas whl包,即可快速完成模型预测。
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- 2020.12.16 添加对cpp预测的tensorRT支持,预测加速更明显。
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- 2020.12.06 添加`SE_HRNet_W64_C_ssld`模型,在ImageNet-1k上Top-1 Acc可达84.75%。
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- 2020.11.23 添加`GhostNet_x1_3_ssld `模型,在ImageNet-1k上Top-1 Acc可达79.38%。
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- 2020.10.20 添加 `Res2Net50_vd_26w_4s_ssld `模型,在ImageNet-1k上Top-1 Acc可达83.1%;添加 `Res2Net101_vd_26w_4s_ssld `模型,在ImageNet-1k上Top-1 Acc可达83.9%。
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- 2020.10.12 添加Paddle-Lite demo。
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- 2020.10.10 添加cpp inference demo,完善`FAQ 30问`教程。
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- 2020.09.17 添加 `HRNet_W48_C_ssld `模型,在ImageNet-1k上Top-1 Acc可达83.62%;添加 `ResNet34_vd_ssld `模型,在ImageNet-1k上Top-1 Acc可达79.72%。
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- [more](./docs/zh_CN/update_history.md)
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- [基于C++预测引擎预测推理](./deploy/cpp_infer/readme.md)
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- [服务化部署](./deploy/hubserving/readme.md)
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- [端侧部署](./deploy/lite/readme.md)
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- [whl包预测](./docs/zh_CN/whl.md)
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- [模型量化压缩](docs/zh_CN/extension/paddle_quantization.md)
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- 高阶使用
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- [知识蒸馏](./docs/zh_CN/advanced_tutorials/distillation/distillation.md)
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# Release Notes
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- 2021.01.08
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* Add support for whl package and its usage, Model inference can be done by simply install paddleclas using pip.
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- 2020.12.16
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* Add support for TensorRT when using cpp inference to obain more obvious acceleration.
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# 更新日志
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- 2021.01.08
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* 添加whl包及其使用说明,直接安装paddleclas whl包,即可快速完成模型预测。
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- 2020.12.16
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* 添加对cpp预测的tensorRT支持,预测加速更明显。
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