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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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@sum_tech · Post #113 · 12/09/2024, 02:19 AM

Рекомендуем всем ИТ-профессионалам иногда читать прекрасный канал "В мире больших данных". Нестандартный взгляд на базы данных и современное состояние ИТ в целом. #партнеры#dbms#рекомендуем

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@githubtrending · Post #15580 · 03/23/2026, 11:30 AM

#go#cli#database#database_management#dbms#environment#local#postgres#postgresql#supabase Supabase CLI lets you run Supabase locally, manage database migrations, deploy functions, generate types from your schema, and make secure API calls. Install easily via npm (`npm i supabase --save-dev`), Homebrew, Scoop, or binaries for any OS, then run `supabase init` and `supabase start` to launch your full stack with local URLs and keys. This benefits you by speeding up development, testing changes offline without cloud costs, ensuring type safety, and simplifying CI/CD for reliable deploys. https://github.com/supabase/cli