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			Merge branch 'master' of https://github.com/alibaba/MNN
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			@ -14,9 +14,11 @@ The design principles and performance data of MNN has been published in an MLSys
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      year = {2020}
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    }
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## Documentation
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## Documentation and Tools
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MNN's docs are in placed in [Yuque docs here](https://www.yuque.com/mnn/en). 
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MNN Workbench could be downloaded from [MNN's homepage](http://www.mnn.zone), which provides pretrained models, visualized training tools, and one-click deployment of models to devices.
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## Key Features
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### High performance
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- Implements core computing with lots of optimized assembly code to make full use of the ARM CPU.
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			@ -14,9 +14,11 @@ MNN的架构设计理念与性能数据在MLSys 2020上面发表。Paper [在此
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      year = {2020}
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## 文档
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## 文档与工具
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MNN的使用文档统一放在语雀,请移步至[语雀文档](https://www.yuque.com/mnn/cn)。
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[MNN官网](http://www.mnn.zone)上还可以下载MNN团队全新力作MNN工作台,涵盖开箱即用模型、可视化训练等工具,更可以一键部署到多端设备。
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## MNN 特色
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### 高性能
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- 不依赖任何第三方计算库,依靠大量手写汇编实现核心运算,充分发挥ARM CPU的算力。
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