DeepSeek v3 | #ai #2024 #genai

Technical Report: https://arxiv.org/pdf/2412.19437 Github: https://github.com/deepseek-ai/DeepSe... 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 #ai, #artificialintelligence, #arxiv, #research, #paper, #publication, #llm, #genai, #generativeai, #largevisualmodels, #largelanguagemodels, #largemultimodalmodels, #nlp, #text, #machinelearning, #ml, #nvidia, #openai, #anthropic, #microsoft, .css-j9qmi7{display:-webkit-box;display:-webkit-flex;display:-ms-flexbox;display:flex;-webkit-flex-direction:row;-ms-flex-direction:row;flex-direction:row;font-weight:700;margin-bottom:1rem;margin-top:2.8rem;width:100%;-webkit-box-pack:start;-ms-flex-pack:start;-webkit-justify-content:start;justify-content:start;padding-left:5rem;}@media only screen and (max-width: 599px){.css-j9qmi7{padding-left:0;-webkit-box-pack:center;-ms-flex-pack:center;-webkit-justify-content:center;justify-content:center;}}.css-j9qmi7 svg{fill:#27292D;}.css-j9qmi7 .eagfbvw0{-webkit-align-items:center;-webkit-box-align:center;-ms-flex-align:center;align-items:center;color:#27292D;}