March 2026
Intermediate
504 pages
11h 26m
Korean
Content preview from 파이토치로 배우는 LLM & AI
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319
12
장
추론의 개념
추론의 개념
CHAPTER
12
이 책의 이전 장에서는 파이토치를 사용해 모델을 훈련하는 방법과 이미지 (컴퓨터 비전 ), 텍
스트 콘텐츠(
NLP
), 시퀀스 모델링을 다루는 모델을 만드는 데 중점을 두었습니다. 이후의 장
에서는 훈련된 모델을 사용해 새로운 데이터로부터 예측을 수행하는 방법 (이를
추론
inference
이
라 부릅니다 )과, 특히 텍스트-투-텍스트 및 텍스트-투-이미지 생성형
AI
를 위한 대규모 생
성 모델을 사용하는 내용을 다룹니다.
하지만 본격적인 내용으로 넘어가기 전에 기본 데이터 전송 기술을 이해하는 것이 중요합니다.
훈련을 다룬 장에서 살짝 다루었지만, 머신러닝의 훈련 또는 추론에 더 깊이 들어갈수록 텐서
의 기본 개념을 이해하는 것이 중요합니다.
궁극적으로 어떤 종류의 데이터를 가지고 있든 모델에 전달하려면 텐서로 변환해야 합니다. 마
찬가지로 사용자에게 어떤 형태로 데이터를 보이고 싶든지 간에 모델이 출력하는 결과는 텐서
입니다.
많은 경우
15
장에서 살펴볼
LLM
용
transformers
나
19
장에서 다룰 이미지 생성용
diffusers
와 같은 헬퍼 라이브러리를 사용하게 됩니다. 이런 라이브러리를 사용할 때는 텐서를 직접 다루
지 않지만, 내부적으로는 여전히 텐서를 사용합니다.
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and much more.
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I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.