<?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>LLM 학습 on TechLLM</title><link>https://techllm.github.io/tags/llm-%ED%95%99%EC%8A%B5/</link><description>Recent content in LLM 학습 on TechLLM</description><generator>Hugo</generator><language>ko</language><lastBuildDate>Tue, 26 May 2026 20:10:00 +0900</lastBuildDate><atom:link href="https://techllm.github.io/tags/llm-%ED%95%99%EC%8A%B5/index.xml" rel="self" type="application/rss+xml"/><item><title>LLM 학습 최적화 완전 정복 — 데이터 타입부터 양자화까지</title><link>https://techllm.github.io/posts/efficient-deep-learning-optimization-guide/</link><pubDate>Tue, 26 May 2026 20:10:00 +0900</pubDate><guid>https://techllm.github.io/posts/efficient-deep-learning-optimization-guide/</guid><description>GPT-2 1.5B 모델에 왜 GPU 메모리 24GB가 필요한가? 데이터 타입, 메모리 소비 구조, 양자화 원리를 단계별로 풀어낸 딥러닝 최적화 종합 가이드.</description></item></channel></rss>