<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Quantization on Text Matrix</title><link>https://155a386f.text-matrix.pages.dev/tags/quantization/</link><description>Recent content in Quantization on Text Matrix</description><generator>Hugo</generator><language>zh-cn</language><lastBuildDate>Wed, 08 Apr 2026 23:16:10 +0800</lastBuildDate><atom:link href="https://155a386f.text-matrix.pages.dev/tags/quantization/index.xml" rel="self" type="application/rss+xml"/><item><title>Quantization 量化技术完全指南：从原理到 LLM 实战</title><link>https://155a386f.text-matrix.pages.dev/posts/tech/llm/quantization-llm-model-compression-guide/</link><pubDate>Sun, 29 Mar 2026 23:28:00 +0800</pubDate><guid>https://155a386f.text-matrix.pages.dev/posts/tech/llm/quantization-llm-model-compression-guide/</guid><description>&lt;h1 id="quantization-量化技术完全指南从原理到-llm-实战">Quantization 量化技术完全指南：从原理到 LLM 实战&lt;/h1>
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&lt;p>&lt;strong>目标读者&lt;/strong>：想深入理解量化技术、压缩大模型体积的开发者
&lt;strong>核心问题&lt;/strong>：如何将 159GB 的大模型压缩到能在笔记本运行，同时只损失 5-10% 精度？&lt;/p></description></item></channel></rss>