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DeepSeek-V2: A Strong, Economical, and Efficient Mixture-of-Experts Language Model
May 8, 2024, 4:47 a.m. | DeepSeek-AI
cs.CL updates on arXiv.org arxiv.org
Abstract: We present DeepSeek-V2, a strong Mixture-of-Experts (MoE) language model characterized by economical training and efficient inference. It comprises 236B total parameters, of which 21B are activated for each token, and supports a context length of 128K tokens. DeepSeek-V2 adopts innovative architectures including Multi-head Latent Attention (MLA) and DeepSeekMoE. MLA guarantees efficient inference through significantly compressing the Key-Value (KV) cache into a latent vector, while DeepSeekMoE enables training strong models at an economical cost through sparse …
arxiv cs.ai cs.cl deepseek experts language language model type
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