模型簡介

DeepSeek-R1是一款具有671B參數大小的創新性大語言模型，該模型基于transformer架構，通過對海量語料數據進行預訓練，結合注意力機制，經過監督微調、人類反饋的強化學習等技術進行對齊，具備語義分析、計算推理、問答對話、篇章生成、代碼編寫等多種能力。R1模型在多個NLP基準測試中表現出色，具備較強的泛化能力和適應性。

使用場景

DeepSeek-R1 模型適用于多種場景，包括但不限于：

●文本生成：如自動寫作、內容創作、對話生成等。

●文本分類：如情感分析、主題分類、垃圾郵件檢測等。

●機器翻譯：支持多語言之間的高質量翻譯。

●問答系統：用于智能客服、知識庫問答等場景。

●信息抽取：如實體識別、關系抽取、事件抽取等。

評測效果

在對話模型典型任務方面的評測效果如下：

技術亮點

DeepSeek-R1 的技術亮點包括：

●大規模預訓練：R1 模型在超大規模文本數據上進行預訓練，學習到了豐富的語言知識和模式。

●多任務學習：通過多任務學習框架，R1 模型能夠在不同任務之間共享知識，提升泛化能力。

●自適應微調：R1 模型支持針對特定任務的自適應微調，能夠快速適應新任務和新領域。

●高效推理：R1 模型在推理階段采用了多種優化技術，確保在保持高性能的同時，具備較高的推理效率。

●可解釋性：R1 模型在設計中考慮了可解釋性，能夠提供一定程度的決策解釋，增強用戶信任。

通過這些技術亮點，DeepSeek-R1在自然語言處理領域展現了強大的競爭力和應用潛力。

版本列表

相關資源及引用

相關資源

DeepSeek-R1的使用協議見

相關引用

@misc{deepseekai2025deepseekr1incentivizingreasoningcapability,
      title={DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning}, 
      author={DeepSeek-AI and Daya Guo and Dejian Yang and Haowei Zhang and Junxiao Song and Ruoyu Zhang and Runxin Xu and Qihao Zhu and Shirong Ma and Peiyi Wang and Xiao Bi and Xiaokang Zhang and Xingkai Yu and Yu Wu and Z. F. Wu and Zhibin Gou and Zhihong Shao and Zhuoshu Li and Ziyi Gao and Aixin Liu and Bing Xue and Bingxuan Wang and Bochao Wu and Bei Feng and Chengda Lu and Chenggang Zhao and Chengqi Deng and Chenyu Zhang and Chong Ruan and Damai Dai and Deli Chen and Dongjie Ji and Erhang Li and Fangyun Lin and Fucong Dai and Fuli Luo and Guangbo Hao and Guanting Chen and Guowei Li and H. Zhang and Han Bao and Hanwei Xu and Haocheng Wang and Honghui Ding and Huajian Xin and Huazuo Gao and Hui Qu and Hui Li and Jianzhong Guo and Jiashi Li and Jiawei Wang and Jingchang Chen and Jingyang Yuan and Junjie Qiu and Junlong Li and J. L. Cai and Jiaqi Ni and Jian Liang and Jin Chen and Kai Dong and Kai Hu and Kaige Gao and Kang Guan and Kexin Huang and Kuai Yu and Lean Wang and Lecong Zhang and Liang Zhao and Litong Wang and Liyue Zhang and Lei Xu and Leyi Xia and Mingchuan Zhang and Minghua Zhang and Minghui Tang and Meng Li and Miaojun Wang and Mingming Li and Ning Tian and Panpan Huang and Peng Zhang and Qiancheng Wang and Qinyu Chen and Qiushi Du and Ruiqi Ge and Ruisong Zhang and Ruizhe Pan and Runji Wang and R. J. Chen and R. L. Jin and Ruyi Chen and Shanghao Lu and Shangyan Zhou and Shanhuang Chen and Shengfeng Ye and Shiyu Wang and Shuiping Yu and Shunfeng Zhou and Shuting Pan and S. S. Li and Shuang Zhou and Shaoqing Wu and Shengfeng Ye and Tao Yun and Tian Pei and Tianyu Sun and T. Wang and Wangding Zeng and Wanjia Zhao and Wen Liu and Wenfeng Liang and Wenjun Gao and Wenqin Yu and Wentao Zhang and W. L. Xiao and Wei An and Xiaodong Liu and Xiaohan Wang and Xiaokang Chen and Xiaotao Nie and Xin Cheng and Xin Liu and Xin Xie and Xingchao Liu and Xinyu Yang and Xinyuan Li and Xuecheng Su and Xuheng Lin and X. Q. Li and Xiangyue Jin and Xiaojin Shen and Xiaosha Chen and Xiaowen Sun and Xiaoxiang Wang and Xinnan Song and Xinyi Zhou and Xianzu Wang and Xinxia Shan and Y. K. Li and Y. Q. Wang and Y. X. Wei and Yang Zhang and Yanhong Xu and Yao Li and Yao Zhao and Yaofeng Sun and Yaohui Wang and Yi Yu and Yichao Zhang and Yifan Shi and Yiliang Xiong and Ying He and Yishi Piao and Yisong Wang and Yixuan Tan and Yiyang Ma and Yiyuan Liu and Yongqiang Guo and Yuan Ou and Yuduan Wang and Yue Gong and Yuheng Zou and Yujia He and Yunfan Xiong and Yuxiang Luo and Yuxiang You and Yuxuan Liu and Yuyang Zhou and Y. X. Zhu and Yanhong Xu and Yanping Huang and Yaohui Li and Yi Zheng and Yuchen Zhu and Yunxian Ma and Ying Tang and Yukun Zha and Yuting Yan and Z. Z. Ren and Zehui Ren and Zhangli Sha and Zhe Fu and Zhean Xu and Zhenda Xie and Zhengyan Zhang and Zhewen Hao and Zhicheng Ma and Zhigang Yan and Zhiyu Wu and Zihui Gu and Zijia Zhu and Zijun Liu and Zilin Li and Ziwei Xie and Ziyang Song and Zizheng Pan and Zhen Huang and Zhipeng Xu and Zhongyu Zhang and Zhen Zhang},
      year={2025},
      eprint={2501.12948},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={//arxiv.org/abs/2501.12948}, 
}

免責聲明

DeepSeek-R1模型來源于第三方，本平臺不保證其合規性，請您在使用前慎重考慮，確保合法合規使用并遵守第三方的要求。