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Source channel @githubtrending · Post #15141 · Sep 13

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#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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@bcd8888 · Post #1546 · 08/07/2025, 01:25 PM

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@tribebrook · Post #469 · 10/04/2025, 03:47 PM

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#Mac#清理#GitHub#CleanMyMac#Lemon 🦡 像鼹鼠一样深入挖掘来清理您的 Mac 一；亮点 🐦深度系统清理- 一次性删除隐藏的缓存、日志和临时文件 📦彻底卸载- 清理了 22 个以上位置，而标准卸载只有 1 个，优于 CleanMyMac/Lemon ⚡️快速且轻量- 基于终端，零膨胀，带分页的箭头键导航 🧹海量空间恢复- 回收 100GB 以上的浪费磁盘空间 二；安装 curl -fsSL curl -fsSL https://raw.githubusercontent.com/tw93/mole/main/install.sh | bash 或者通过 Homebrew： brew install tw93/tap/mole GitHub地址：官方 🔔提示：限免，兑换码具有时效性，打开本频道通知，第一时间获取全网资讯！！！ 🏠本消息Via：小小溪 📰群组：homeBrook 📢频道：Home_brook 🤖其他问题（投稿）请Bot：@xia0_bot

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