DeepSeek v3 | #ai #2024 #genai

This research paper introduces DeepSeek-V3, a 671-billion parameter Mixture-of-Experts (MoE) large language model. The paper details DeepSeek-V3's architecture, including its innovative auxiliary-loss-free load balancing strategy and Multi-Token Prediction objective, and its efficient training framework utilizing FP8 precision. Extensive evaluations demonstrate DeepSeek-V3's superior performance across various benchmarks compared to other open-source and some closed-source models, particularly in code and math tasks. The paper also discusses post-training methods like supervised fine-tuning and reinforcement learning, along with deployment strategies and hardware design suggestions. Finally, it acknowledges limitations and suggests future research directions

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