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@@ -50,10 +50,9 @@ Now our developers can acquire Tesla V100 online computing resources for free. I
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[Click here to learn more](https://github.com/PaddlePaddle/Fleet)
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-**Accelerated High-Performance Inference over Ubiquitous Deployments**
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-**High-Performance Inference Engines for Comprehensive Deployment Enviroments**
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PaddlePaddle is not only compatible with other open-source frameworks for models training, but also works well on the ubiquitous developments, varying from platforms to devices. More specifically, PaddlePaddle accelerates the inference procedure with the fastest speed-up. Note that, a recent breakthrough of inference speed has been made by PaddlePaddle on Huawei's Kirin NPU, through the hardware/software co-optimization.
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[Click here to learn more](https://github.com/PaddlePaddle/Paddle-Lite)
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PaddlePaddle is not only compatible with models trained in 3rd party open-source frameworks , but also offers complete inference products for various production scenarios. Our inference product line includes [Paddle Inference](https://paddle-inference.readthedocs.io/en/latest/product_introduction/summary.html): Native inference library for high performance server and cloud inference; [Paddle Serving](https://github.com/PaddlePaddle/Serving): A service-oriented framework suitable for distributed and pipeline productions; [Paddle Lite](https://github.com/PaddlePaddle/Paddle-Lite): Ultra-Lightweight inference engine for mobile and IoT enviroments; [Paddle.js](https://www.paddlepaddle.org.cn/paddle/paddlejs): A frontend inference engine for browser and mini apps. Futhermore, by great amounts of optimization with leading hardwares in each scenarios, Paddle inference engines outperform most of the other mainstream frameworks.
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-**Industry-Oriented Models and Libraries with Open Source Repositories**
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