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Source channel @pythontelegrambotchannel · Post #89 · Oct 7

The v13 release is not just a release either, it is also our official announcement of participation in the annual #hacktoberfest. 💻🥨 We know that we're a few days late to the party, but v13 had to get ready before. 😉 This year, the fest is opt-in for projects and we definitely want to opt into taking part in this great event! If you ever thought about starting coding or giving back to your favourite open source repositories, now is the time! Head over to the hacktoberfest website to learn more about it. We already prepared some issues on our repositories and aim towards opening more issues for starters, but feel free to begin a hunt for improvements and fixes by yourself!

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@githubtrending · Post #15271 · 11/05/2025, 12:30 PM

#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