沙丘社区
论文

Intern-S1-Pro：万亿规模的科学多模态基础模型

Intern-S1-Pro: Scientific Multimodal Foundation Model at Trillion Scale

Yicheng Zou; Dongsheng Zhu; Lin Zhu; Tong Zhu; Yunhua Zhou; Peiheng Zhou; Xinyu Zhou; Dongzhan Zhou; Zhiwang Zhou; Yuhao Zhou; Bowen Zhou; Zhanping Zhong; Zhijie Zhong; Haiteng Zhao; Penghao Zhao; Xiaomeng Zhao; Zhiyuan Zhao; Yechen Zhang; Jin Zhang; Wenwei Zhang; Hongjie Zhang; Zhuo Zhang; Wenlong Zhang; Bo Zhang; Chao Zhang; Chen Zhang; Yuhang Zang; Fei Yuan; Jiakang Yuan; Jiashuo Yu; Jinhui Yin; Haochen Ye; Qian Yao; Bowen Yang; Danni Yang; Kaichen Yang; Ziang Yan; Jun Xu; Yicheng Xu; Wanghan Xu; Xuenan Xu; Chao Xu; Ruiliang Xu; Shuhao Xing; Long Xing; Xinchen Xie; Ling-I Wu; Zijian Wu; Zhenyu Wu; Lijun Wu; Yue Wu; Jianyu Wu; Wen Wu; Fan Wu; Xilin Wei; Qi Wei; Bingli Wang; Rui Wang; Ziyi Wang; Zun Wang; Yi Wang; Haomin Wang; Yizhou Wang; Lintao Wang; Yiheng Wang; Longjiang Wang; Bin Wang; Jian Tong; Zhongbo Tian; Huanze Tang; Chen Tang; Shixiang Tang; Yu Sun; Qiushi Sun; Xuerui Su; Qisheng Su; Chenlin Su; Demin Song; Jin Shi; Fukai Shang; Yuchen Ren; Pengli Ren; Xiaoye Qu; Yuan Qu; Jiantao Qiu; Yu Qiao; Biqing Qi; Runyu Peng; Tianshuo Peng; Jiahui Peng; Qizhi Pei; Zhuoshi Pan; Linke Ouyang; Wenchang Ning; Yichuan Ma; Zerun Ma; Ningsheng Ma; Runyuan Ma; Chengqi Lyu; Haijun Lv; Han Lv; Lindong Lu; Kuikun Liu; Jiangning Liu; Yuhong Liu; Kai Liu; Hongwei Liu; Zhoumianze Liu; Mengjie Liu; Ziyu Liu; Wenran Liu; Yang Liu; Liwei Liu; Kaiwen Liu; Junyao Lin; Junming Lin; Tianyang Lin; Dahua Lin; Jianze Liang; Linyang Li; Peiji Li; Zonglin Li; Zehao Li; Pengze Li; Guoyan Li; Lingkai Kong; Linglin Jing; Zhenjiang Jin; Feifei Jiang; Qian Jiang; Junhao Huang; Zixian Huang; Haian Huang; Zhouqi Hua; Ermo Hua; Han Hu; Linfeng Hou; Yinan He; Conghui He; Tianyao He; Xu Guo; Qipeng Guo; Aijia Guo; Yuzhe Gu; Lixin Gu; Jingyang Gong; Qiming Ge; Jiaye Ge; Songyang Gao; Jianfei Gao; Xinyu Fang; Caihua fan; Yue Fan; Yanhui Duan; Zichen Ding; Shengyuan Ding; Ning Ding; Xuanlang Dai; Erfei Cui; Ganqu Cui; Pei Chu; Tao Chu; Guangran Cheng; Yu Cheng; Kai Chen; Yongkang Chen; Chiyu Chen; Guanzhou Chen; Qiaosheng Chen; Sitao Chen; Xin Chen; Haojiong Chen; Yicheng Chen; Weihan Cao; Yuhang Cao; Qinglong Cao; Lei Bai
应用与实践通用理解与问答

摘要

我们推出了 Intern-S1-Pro，这是第一个万亿参数科学多模态基础模型。该模型扩展到前所未有的规模，在一般领域和科学领域提供了全面的增强。除了更强的推理和图像文本理解能力之外，其智能还通过先进的代理功能得到增强。同时，其科学专业知识得到了极大扩展，掌握了化学、材料、生命科学和地球科学等关键科学领域的 100 多项专业任务。 XTuner 和 LMDeploy 强大的基础设施支持使得实现如此大规模成为可能，这有助于在 1 万亿参数级别进行高效的强化学习 (RL) 训练，同时确保训练和推理之间严格的精度一致性。通过无缝集成这些进步，Intern-S1-Pro 进一步加强了通用智能和专业智能的融合，作为专业通才，展示了其在通用能力开源模型中的顶级地位，同时在专业科学任务的深度上超越了专有模型。