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Jamba

상태공간 모델과 Transformer를 혼합한 오픈웨이트 모델

AI21 Labs 모델 공개 가중치
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무엇인가

Jamba is an open-weight model AI21 Labs released in March 2024, interleaving Mamba state-space layers with Transformer attention layers inside one mixture-of-experts architecture. AI21 Labs was founded in Tel Aviv in 2017 by Amnon Shashua and others. This hybrid design holds long context while cutting memory and compute relative to a pure-attention model. Jamba ships as a 52B-parameter MoE that activates about 12B per token, with a context window in the 256K range.

기억할 만한 이유

It replaced most attention layers with state-space layers, testing whether a non-pure-Transformer architecture can save compute at long context — a concrete instance of hybrid architectures entering open-weight models.

주요 사양

Parameters
52B (MoE, ~12B active)
Context window
256K tokens
Architecture
Mamba state-space layers interleaved with Transformer layers
Open weights
Yes

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관련 개념

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