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Source channel @githubtrending · Post #14902 · Jul 3

#go#tailscale#tailscale_control_server#tailscale_server#wireguard Headscale is an open-source, self-hosted alternative to the Tailscale control server, letting you create your own private VPN network using Wireguard technology. It supports key Tailscale features like node registration, DNS, file sharing (Taildrop), access control lists (ACLs), and more, making it ideal for personal or small group use. By running Headscale yourself, you gain full control over your network without relying on Tailscale’s servers, enhancing privacy and customization. You can manage access precisely with ACLs, tag devices for group policies, and use modern VPN benefits like NAT traversal and secure connections between your devices[1][3][5]. This helps you securely connect and control your devices in a private network tailored to your needs. https://github.com/juanfont/headscale

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

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#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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