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Изходен канал @clockstackwheels · Post #108 · 21.11

Подсказали крутой сервис для централизации ссылок на подкаст. Просто вводишь название и всё, сервис сам с помощью API поиска ищет твой подкаст везде. Вот например, мой: https://podcast.ru/1585776330 Так я узнал, что меня раскатали и на Apple Podcasts тоже (я пользуюсь автоматизированным сервисом раскатки, и там написано, что Apple только после модерации, странно). #podcast

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@githubtrending · Post #15271 · 05.11.2025 г., 12:30

#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