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# Gemma2 [[gemma2]]
## 개요 [[overview]]
Gemma2 모델은 Google의 Gemma2 팀이 작성한 [Gemma2: Open Models Based on Gemini Technology and Research](https://blog.google/technology/developers/google-gemma-2/)에서 제안되었습니다.
파라미터 크기가 각각 90억(9B)과 270억(27B)인 두 가지 Gemma2 모델이 출시되었습니다.
블로그 게시물의 초록은 다음과 같습니다:
*이제 우리는 전 세계의 연구자와 개발자들에게 Gemma 2를 공식적으로 출시합니다. 90억(9B)과 270억(27B) 파라미터 크기로 제공되는 Gemma 2는 1세대보다 더 높은 성능과 추론 효율성을 제공하며, 상당한 안전성 향상을 포함하고 있습니다. 사실 270억 규모의 모델은 크기가 두 배 이상인 모델과 비교해도 경쟁력 있는 대안을 제공하며, 이는 작년 12월까지만 해도 독점 모델에서만 가능했던 성능을 제공합니다.*
팁:
- 원본 체크포인트는 변환 스크립트 `src/transformers/models/Gemma2/convert_Gemma2_weights_to_hf.py`를 사용하여 변환할 수 있습니다.
이 모델은 [Arthur Zucker](https://huggingface.co/ArthurZ), [Pedro Cuenca](https://huggingface.co/pcuenq), [Tom Arsen]()이 기여했습니다.
## Gemma2Config [[transformers.Gemma2Config]]
[[autodoc]] Gemma2Config
## Gemma2Model [[transformers.Gemma2Model]]
[[autodoc]] Gemma2Model
- forward
## Gemma2ForCausalLM [[transformers.Gemma2ForCausalLM]]
[[autodoc]] Gemma2ForCausalLM
- forward
## Gemma2ForSequenceClassification [[transformers.Gemma2ForSequenceClassification]]
[[autodoc]] Gemma2ForSequenceClassification
- forward
## Gemma2ForTokenClassification [[transformers.Gemma2ForTokenClassification]]
[[autodoc]] Gemma2ForTokenClassification
- forward