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Source channel @githubtrending · Post #15141 · Sep 13

#python#large_language_models#machine_learning_systems#natural_language_processing Flash Linear Attention (FLA) is a fast, memory-efficient library for advanced linear attention models used in transformers, written in PyTorch and Triton, and compatible with NVIDIA, AMD, and Intel GPUs. It offers many state-of-the-art linear attention models and fused modules that speed up training and reduce memory use. You can easily replace standard attention layers in your models with FLA’s efficient versions, improving training and inference speed, especially for long sequences. FLA supports hybrid models mixing linear and standard attention, and integrates with Hugging Face Transformers for easy use and evaluation. This helps you train and run large language models faster and with less memory, making your AI projects more efficient and scalable. https://github.com/fla-org/flash-linear-attention

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@githubtrending · Post #14989 · 07/23/2025, 11:30 AM

#c_lang#bluetooth#bluetooth_le#embedded#embedded_c#iot#mcu#microcontroller#real_time#rtos#zephyr#zephyr_rtos#zephyros Zephyr is a free, open-source real-time operating system (RTOS) designed for small, resource-limited devices like sensors, wearables, and IoT gateways. It supports many hardware types such as ARM, Intel x86, and RISC-V, making it flexible for different projects. Zephyr is modular, so you can include only what you need, saving memory and power. It focuses on security with features like memory protection and secure boot. It also offers built-in networking and tools for easy development and testing. This helps you build reliable, fast, and secure embedded systems efficiently, especially for IoT and real-time applications[1][2][3]. https://github.com/zephyrproject-rtos/zephyr