April 2026
Intermediate
592 pages
13h 28m
Korean
Content preview from 에이전트 시대의 AI 시스템 설계
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148
에이전트 시대의 AI 시스템 설계
다음으로 조정하고자 하는 모델을 준비한다.
model = AutoModelForCausalLM.from_pretrained(MODEL_ID)
tokenizer = AutoTokenizer.from_pretrained(MODEL_ID)
마지막으로, 데이터셋과 모델로
DPOTrainer
를 호출해서 훈련을 시작한다.
trainer = DPOTrainer(model=model, ..., train_dataset=train_dataset)
trainer.train()
우리의 경우
vCPU
8
개와
L4
GPU
가 장착된 컴퓨터에서 예시
100
개로 훈련을 마치는 데 약
3
분이 걸렸다.
인퍼런스
로컬에서 훈련한 모델로 파이프라인을 생성한다. 허깅 페이스 허브에 있는 모델을 사용할 때와
별반 다르지 않다.
pipe = pipeline(
task="text-generation",
model="ClassifiedAds-DPO",
use_fast=True,
kwargs={
"return_full_text": False,
},
model_kwargs={}
)
다음은 이 파이프라인을 이용해서 새 콘텐츠를 생성하는 함수이다. 프롬프트 자체는 이전과 동
일하다.
def create_classified_ad(item: str, price: str) ->
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O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.Julian F.
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.