Zobrazeno 1 - 10
of 312
pro vyhledávání: '"HUANG Panpan"'
Publikováno v:
Zhongguo shipin weisheng zazhi, Vol 36, Iss 4, Pp 414-419 (2024)
ObjectiveTo analyze the pollution status and exposure risks of heavy metals by three edible traditional Chinese herbal medicine, such as ganoderma lucidum, dendrobium officinale, and American ginseng in Guangdong Province.MethodsFresh and dried
Externí odkaz:
https://doaj.org/article/70d8790f1c424abea39e461264c9cf55
Publikováno v:
Acta Biochimica et Biophysica Sinica, Vol 55, Pp 842-852 (2023)
Osteosarcoma (OS) is the most common primary bone cancer in children and adolescents. In clinical treatments, the insensitivity of OS to conventional radiotherapy regimens significantly contributes to poor patient prognosis and survival. EXO1 is resp
Externí odkaz:
https://doaj.org/article/fce5f0ffc8684743adb182145e42368d
Autor:
TU Hongwei, LIU Zhiting, ZHONG Ruoxi, WU Wei, CHI Lan, GAN Ping, KE Qiuyi, HUANG Panpan, CHEN Hongsheng, YAN Weina
Publikováno v:
Zhongguo shipin weisheng zazhi, Vol 34, Iss 4, Pp 673-679 (2022)
ObjectiveTo reveal the effects of specific factors on aflatoxin B1 (AFB1) contamination in peanut oil and the status of AFB1 contamination in peanut oil in Guangdong Province from 2017 to 2018 was taken as an example.MethodsA total of 637 peanut
Externí odkaz:
https://doaj.org/article/493270ff726242c6a4b74dd26d63279e
Autor:
An, Wei, Bi, Xiao, Chen, Guanting, Chen, Shanhuang, Deng, Chengqi, Ding, Honghui, Dong, Kai, Du, Qiushi, Gao, Wenjun, Guan, Kang, Guo, Jianzhong, Guo, Yongqiang, Fu, Zhe, He, Ying, Huang, Panpan, Li, Jiashi, Liang, Wenfeng, Liu, Xiaodong, Liu, Xin, Liu, Yiyuan, Liu, Yuxuan, Lu, Shanghao, Lu, Xuan, Nie, Xiaotao, Pei, Tian, Qiu, Junjie, Qu, Hui, Ren, Zehui, Sha, Zhangli, Su, Xuecheng, Sun, Xiaowen, Tan, Yixuan, Tang, Minghui, Wang, Shiyu, Wang, Yaohui, Wang, Yongji, Xie, Ziwei, Xiong, Yiliang, Xu, Yanhong, Ye, Shengfeng, Yu, Shuiping, Zha, Yukun, Zhang, Liyue, Zhang, Haowei, Zhang, Mingchuan, Zhang, Wentao, Zhang, Yichao, Zhao, Chenggang, Zhao, Yao, Zhou, Shangyan, Zhou, Shunfeng, Zou, Yuheng
The rapid progress in Deep Learning (DL) and Large Language Models (LLMs) has exponentially increased demands of computational power and bandwidth. This, combined with the high costs of faster computing chips and interconnects, has significantly infl
Externí odkaz:
http://arxiv.org/abs/2408.14158
Autor:
HU Yan, HUANG PanPan
Publikováno v:
Jixie qiangdu, Vol 42, Pp 919-924 (2020)
The catenary of full-compensated simple chain suspension widely used at present china railway was taken as the research object,and a dynamic simulation model of pantograph-catenary was established using the finite element method. The pantograph and c
Externí odkaz:
https://doaj.org/article/c745f421947e45d485d54a6439771a6d
Autor:
DeepSeek-AI, Liu, Aixin, Feng, Bei, Wang, Bin, Wang, Bingxuan, Liu, Bo, Zhao, Chenggang, Dengr, Chengqi, Ruan, Chong, Dai, Damai, Guo, Daya, Yang, Dejian, Chen, Deli, Ji, Dongjie, Li, Erhang, Lin, Fangyun, Luo, Fuli, Hao, Guangbo, Chen, Guanting, Li, Guowei, Zhang, H., Xu, Hanwei, Yang, Hao, Zhang, Haowei, Ding, Honghui, Xin, Huajian, Gao, Huazuo, Li, Hui, Qu, Hui, Cai, J. L., Liang, Jian, Guo, Jianzhong, Ni, Jiaqi, Li, Jiashi, Chen, Jin, Yuan, Jingyang, Qiu, Junjie, Song, Junxiao, Dong, Kai, Gao, Kaige, Guan, Kang, Wang, Lean, Zhang, Lecong, Xu, Lei, Xia, Leyi, Zhao, Liang, Zhang, Liyue, Li, Meng, Wang, Miaojun, Zhang, Mingchuan, Zhang, Minghua, Tang, Minghui, Li, Mingming, Tian, Ning, Huang, Panpan, Wang, Peiyi, Zhang, Peng, Zhu, Qihao, Chen, Qinyu, Du, Qiushi, Chen, R. J., Jin, R. L., Ge, Ruiqi, Pan, Ruizhe, Xu, Runxin, Chen, Ruyi, Li, S. S., Lu, Shanghao, Zhou, Shangyan, Chen, Shanhuang, Wu, Shaoqing, Ye, Shengfeng, Ma, Shirong, Wang, Shiyu, Zhou, Shuang, Yu, Shuiping, Zhou, Shunfeng, Zheng, Size, Wang, T., Pei, Tian, Yuan, Tian, Sun, Tianyu, Xiao, W. L., Zeng, Wangding, An, Wei, Liu, Wen, Liang, Wenfeng, Gao, Wenjun, Zhang, Wentao, Li, X. Q., Jin, Xiangyue, Wang, Xianzu, Bi, Xiao, Liu, Xiaodong, Wang, Xiaohan, Shen, Xiaojin, Chen, Xiaokang, Chen, Xiaosha, Nie, Xiaotao, Sun, Xiaowen, Wang, Xiaoxiang, Liu, Xin, Xie, Xin, Yu, Xingkai, Song, Xinnan, Zhou, Xinyi, Yang, Xinyu, Lu, Xuan, Su, Xuecheng, Wu, Y., Li, Y. K., Wei, Y. X., Zhu, Y. X., Xu, Yanhong, Huang, Yanping, Li, Yao, Zhao, Yao, Sun, Yaofeng, Li, Yaohui, Wang, Yaohui, Zheng, Yi, Zhang, Yichao, Xiong, Yiliang, Zhao, Yilong, He, Ying, Tang, Ying, Piao, Yishi, Dong, Yixin, Tan, Yixuan, Liu, Yiyuan, Wang, Yongji, Guo, Yongqiang, Zhu, Yuchen, Wang, Yuduan, Zou, Yuheng, Zha, Yukun, Ma, Yunxian, Yan, Yuting, You, Yuxiang, Liu, Yuxuan, Ren, Z. Z., Ren, Zehui, Sha, Zhangli, Fu, Zhe, Huang, Zhen, Zhang, Zhen, Xie, Zhenda, Hao, Zhewen, Shao, Zhihong, Wen, Zhiniu, Xu, Zhipeng, Zhang, Zhongyu, Li, Zhuoshu, Wang, Zihan, Gu, Zihui, Li, Zilin, Xie, Ziwei
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 128
Externí odkaz:
http://arxiv.org/abs/2405.04434
Autor:
Dai, Damai, Deng, Chengqi, Zhao, Chenggang, Xu, R. X., Gao, Huazuo, Chen, Deli, Li, Jiashi, Zeng, Wangding, Yu, Xingkai, Wu, Y., Xie, Zhenda, Li, Y. K., Huang, Panpan, Luo, Fuli, Ruan, Chong, Sui, Zhifang, Liang, Wenfeng
In the era of large language models, Mixture-of-Experts (MoE) is a promising architecture for managing computational costs when scaling up model parameters. However, conventional MoE architectures like GShard, which activate the top-$K$ out of $N$ ex
Externí odkaz:
http://arxiv.org/abs/2401.06066
Autor:
DeepSeek-AI, Bi, Xiao, Chen, Deli, Chen, Guanting, Chen, Shanhuang, Dai, Damai, Deng, Chengqi, Ding, Honghui, Dong, Kai, Du, Qiushi, Fu, Zhe, Gao, Huazuo, Gao, Kaige, Gao, Wenjun, Ge, Ruiqi, Guan, Kang, Guo, Daya, Guo, Jianzhong, Hao, Guangbo, Hao, Zhewen, He, Ying, Hu, Wenjie, Huang, Panpan, Li, Erhang, Li, Guowei, Li, Jiashi, Li, Yao, Li, Y. K., Liang, Wenfeng, Lin, Fangyun, Liu, A. X., Liu, Bo, Liu, Wen, Liu, Xiaodong, Liu, Xin, Liu, Yiyuan, Lu, Haoyu, Lu, Shanghao, Luo, Fuli, Ma, Shirong, Nie, Xiaotao, Pei, Tian, Piao, Yishi, Qiu, Junjie, Qu, Hui, Ren, Tongzheng, Ren, Zehui, Ruan, Chong, Sha, Zhangli, Shao, Zhihong, Song, Junxiao, Su, Xuecheng, Sun, Jingxiang, Sun, Yaofeng, Tang, Minghui, Wang, Bingxuan, Wang, Peiyi, Wang, Shiyu, Wang, Yaohui, Wang, Yongji, Wu, Tong, Wu, Y., Xie, Xin, Xie, Zhenda, Xie, Ziwei, Xiong, Yiliang, Xu, Hanwei, Xu, R. X., Xu, Yanhong, Yang, Dejian, You, Yuxiang, Yu, Shuiping, Yu, Xingkai, Zhang, B., Zhang, Haowei, Zhang, Lecong, Zhang, Liyue, Zhang, Mingchuan, Zhang, Minghua, Zhang, Wentao, Zhang, Yichao, Zhao, Chenggang, Zhao, Yao, Zhou, Shangyan, Zhou, Shunfeng, Zhu, Qihao, Zou, Yuheng
The rapid development of open-source large language models (LLMs) has been truly remarkable. However, the scaling law described in previous literature presents varying conclusions, which casts a dark cloud over scaling LLMs. We delve into the study o
Externí odkaz:
http://arxiv.org/abs/2401.02954
Publikováno v:
In Heliyon 15 November 2024 10(21)
Publikováno v:
In Wear 1 June 2024 546-547