# Efficient Computing

Kanana is a series of bilingual large language models developed by Kakao, excelling in Korean tasks while maintaining competitiveness in English tasks. The 2.1b version is the lightweight base model of this series.

Kanana is a bilingual (Korean/English) language model series developed by Kakao. This 2.1B parameter version outperforms similar models in Korean while maintaining efficient computational costs.

A large language model based on LLaMA-2-7B with activation sparsification, achieving high sparsity (89.32%) while maintaining original performance through the ProSparse method

MoLM is a series of language models based on the Mixture of Experts (MoE) architecture. The 700M-4B version has a total of 4 billion parameters, with computational consumption equivalent to a dense model of 700 million parameters.