<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:content="http://purl.org/rss/1.0/modules/content/"><channel><title>模型量化 on 硅基 AGI · 智能体学习与测评</title><link>https://guijiagi.com/tags/%E6%A8%A1%E5%9E%8B%E9%87%8F%E5%8C%96/</link><description>Recent content in 模型量化 on 硅基 AGI · 智能体学习与测评</description><generator>Hugo</generator><language>zh-cn</language><copyright>本站内容采用 CC BY-NC-SA 4.0 国际许可协议授权</copyright><lastBuildDate>Thu, 16 Jul 2026 10:09:00 +0800</lastBuildDate><atom:link href="https://guijiagi.com/tags/%E6%A8%A1%E5%9E%8B%E9%87%8F%E5%8C%96/index.xml" rel="self" type="application/rss+xml"/><item><title>边缘AI部署实战：在资源受限设备上运行大模型</title><link>https://guijiagi.com/posts/b2-00a223f8/</link><pubDate>Thu, 16 Jul 2026 10:09:00 +0800</pubDate><guid>https://guijiagi.com/posts/b2-00a223f8/</guid><description>探讨在手机、边缘服务器等资源受限设备上部署大模型的技术方案，涵盖模型压缩、推理引擎选择与硬件适配</description></item><item><title>端侧大模型部署：手机/Edge/IoT全场景选型</title><link>https://guijiagi.com/posts/edge-device-llm-deployment/</link><pubDate>Tue, 30 Jun 2026 11:05:00 +0800</pubDate><guid>https://guijiagi.com/posts/edge-device-llm-deployment/</guid><description>端侧大模型部署全场景指南，覆盖手机、边缘设备和IoT的模型选型与优化</description></item><item><title>端侧大模型部署：手机/Edge/IoT 全场景选型</title><link>https://guijiagi.com/posts/edge-device-llm-deployment-mobile-iot-selection/</link><pubDate>Sun, 28 Jun 2026 10:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/edge-device-llm-deployment-mobile-iot-selection/</guid><description>端侧大模型在手机、边缘设备、IoT场景的全面选型指南与部署方案</description></item><item><title>模型量化技术原理与实践</title><link>https://guijiagi.com/posts/model-quantization-techniques-2026/</link><pubDate>Sat, 27 Jun 2026 15:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/model-quantization-techniques-2026/</guid><description>深入解析大模型量化技术原理，从对称量化到混合精度的完整实践指南</description></item></channel></rss>