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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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@githubtrending · Post #15087 · 08/23/2025, 12:00 PM

#shell#cassowary#docker#freerdp#gnome#hacktoberfest#integration#kde#libvirt#linux#linux_app#nautilus#nix_flake#podman#qemu#qemu_kvm#seamless#winapps#windows#wine#xfce You can run Windows applications like Microsoft Office and Adobe Creative Cloud directly on your Linux desktop (KDE, GNOME, or XFCE) as if they were native apps using WinApps. It works by running Windows inside a virtual machine (using Docker, Podman, or libvirt) and then showing Windows apps seamlessly on Linux with FreeRDP. Your Linux home folder is accessible in Windows, and you can right-click files in Linux to open them with Windows apps. This lets you use all Windows programs without leaving Linux, improving productivity and convenience without needing dual boot or separate hardware. https://github.com/winapps-org/winapps