<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Machine-Learning on Tony老师的博客</title><link>https://blog.tanteng.space/tags/machine-learning/</link><description>Recent content in Machine-Learning on Tony老师的博客</description><generator>Hugo</generator><language>zh</language><lastBuildDate>Sun, 01 Mar 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://blog.tanteng.space/tags/machine-learning/index.xml" rel="self" type="application/rss+xml"/><item><title>大模型是怎么炼成的</title><link>https://blog.tanteng.space/posts/llm-training-full-stack/</link><pubDate>Sun, 01 Mar 2026 00:00:00 +0000</pubDate><guid>https://blog.tanteng.space/posts/llm-training-full-stack/</guid><description>&lt;p&gt;大语言模型（LLM）的训练与部署，是一个横跨数据工程、分布式系统、GPU 架构、强化学习、推理服务等多个领域的综合工程。本文把从原始数据到线上推理的完整技术栈梳理清楚，让你对&amp;quot;模型是如何炼成的、又是如何跑起来的&amp;quot;有一个系统性认知。&lt;/p&gt;</description></item></channel></rss>