<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>SFT - 标签 - 探索云原生</title><link>https://www.lixueduan.com/tags/sft/</link><description>探索云原生（微信公众号：探索云原生）,是意琦行的技术博客。一个云原生打工人的探索之路。从容器与编排出发，现主要折腾云原生AI基础设施：GPU资源化、编排调度、模型服务与可观测性等等。坚持分享踩坑实录与最佳实践。</description><generator>Hugo 0.149.0 &amp; FixIt v0.4.0-alpha-20250831070510-5a66a050</generator><language>zh-CN</language><managingEditor>xueduan.li@gmail.com (意琦行)</managingEditor><webMaster>xueduan.li@gmail.com (意琦行)</webMaster><lastBuildDate>Wed, 18 Sep 2024 22:00:00 +0000</lastBuildDate><atom:link href="https://www.lixueduan.com/tags/sft/index.xml" rel="self" type="application/rss+xml"/><item><title>大模型微调实战：基于 LLaMAFactory 通过 LoRA 微调修改模型自我认知</title><link>https://www.lixueduan.com/posts/ai/05-finetune-llamafactory/</link><pubDate>Wed, 18 Sep 2024 22:00:00 +0000</pubDate><author>xueduan.li@gmail.com (意琦行)</author><guid>https://www.lixueduan.com/posts/ai/05-finetune-llamafactory/</guid><category domain="https://www.lixueduan.com/categories/ai/">AI</category><description>&lt;p&gt;&lt;img loading="lazy" src='https://img.lixueduan.com/ai/cover/finetune-by-llamafactory.png' alt="finetune-by-llamafactory.png"&gt;&lt;/p&gt;
&lt;p&gt;本文主要分享如何使用 LLaMAFactory 实现大模型微调，基于 Qwen1.5-1.8B-Chat 模型进行 LoRA 微调，修改模型自我认知。&lt;/p&gt;</description></item><item><title>GPT 是如何炼成的：大模型微调基础概念指北</title><link>https://www.lixueduan.com/posts/ai/04-finetune-concept/</link><pubDate>Tue, 10 Sep 2024 00:00:00 +0000</pubDate><author>xueduan.li@gmail.com (意琦行)</author><guid>https://www.lixueduan.com/posts/ai/04-finetune-concept/</guid><category domain="https://www.lixueduan.com/categories/ai/">AI</category><description>&lt;p&gt;&lt;img loading="lazy" src='https://img.lixueduan.com/ai/cover/finetune-concept.png' alt="finetune-concept.png"&gt;&lt;/p&gt;
&lt;p&gt;本文主要分享一下大模型微调相关的基本概念，包括大模型(GPT)训练流程、微调(SFT)方法&amp;amp;分类&amp;amp;框架&amp;amp;最佳实践、强化学习(RLHF)，最后则是分享了如何训练垂直领域大模型。&lt;/p&gt;</description></item></channel></rss>