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Source channel @githubtrending · Post #15271 · Nov 5

#cplusplus#arm#baidu#deep_learning#embedded#fpga#mali#mdl#mobile#mobile_deep_learning#neural_network Paddle Lite is a lightweight, high-performance deep learning inference framework designed to run AI models efficiently on mobile, embedded, and edge devices. It supports multiple platforms like Android, iOS, Linux, Windows, and macOS, and languages including C++, Java, and Python. You can easily convert models from other frameworks to PaddlePaddle format, optimize them for faster and smaller deployment, and run them with ready-made examples. This helps you deploy AI applications quickly on various devices with low memory use and fast speed, making it ideal for real-time, resource-limited environments. It also supports many hardware accelerators for better performance. https://github.com/PaddlePaddle/Paddle-Lite

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djangoproject

@djangoproject · Post #306 · 04/25/2017, 09:49 AM

http://aiohttp.readthedocs.io/en/stable/deployment.html There are several options for #aiohttp server deployment: Standalone server Running a pool of backend servers behind of #nginx, #HAProxy or other reverse proxy server Using #gunicorn behind of reverse proxy