March 2026
Intermediate
504 pages
11h 26m
Korean
Content preview from 파이토치로 배우는 LLM & AI
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367
15
장
트랜스포머와 transformers
트랜스포머와
transformers
CHAPTER
15
2017
년
Ashish
Vaswani
등이 쓴 논문 ‘
Attention
Is
All
You
Need
’
1
은
AI
분야를 완전히
바꾸어 놓았습니다. 합성곱 (
4
장)과 순환 신경망 (
9
장) 구조의 진화와 같이 이 논문의 초록은
가볍고 단순한 것을 나타냅니다. 하지만 이 논문의 영향은 혁신적이었습니다.
NLP
에서 시작해
서
AI
분야를 혁신했습니다. 저자들은 이 방식이 단순하다고 주장하지만 코드로 구현하는 것은
복잡했습니다. 머신러닝 구조에 대한 새로운 접근 방식인
트랜스포머
Transformer
가 있습니다.
이 장에서는 고수준에서 트랜스포머 이면의 아이디어를 살펴보고, 트랜스포머의 세 가지 주요
구조인 인코더, 디코더, 인코더-디코더를 설명합니다. 이 구조의 동작 방식에 대해 매우 고수
준에서 다룬다는 것을 유의하세요. 이에 대해 깊이 다루려면 하나의 장이 아니라 몇 권의 책이
필요할 것입니다.
2
그다음 트랜스포머 기반 모델을 쉽게 사용하게 해 주는 허깅 페이스 라이브러리
transformers
를 살펴보겠습니다.
transformers
이전에는 논문을 읽고 대부분 세부 사항을 직접 구현해야
했습니다. 허깅 페이스
transformers
라이브러리는 트랜스포머 ...
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