이 장에서는 트랜스포머 아키텍처의 다양한 구성 요소를 상세히 다뤘습니다. 셀프 어텐션, 피
드포워드 네트워크, 위치 인코딩, 층 정규화 등이 여기에 포함됩니다. 또한 인코더 전용, 인코
더-디코더, 디코더 전용,
MoE
모델과 같은 여러 변형과 구성도 알아봤습니다. 마지막으로, 언
어 모델 지식을 종합해 처음부터 자체 모델을 훈련하는 방법과 더 효율적인 학습을 위한 도메
인 특화 언어를 설계하는 방법을 다뤘습니다.
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