Python-文本匹配的相关模型DSSMESIMABCNNBIMPM等数据集为LCQMC官方数据

上传者: 39840650 | 上传时间: 2021-09-19 20:55:35 | 文件大小: 10.25MB | 文件类型: ZIP
文本匹配的相关模型DSSM,ESIM,ABCNN,BIMPM等,数据集为LCQMC官方数据

文件下载

资源详情

[{"title":"( 51 个子文件 10.25MB ) Python-文本匹配的相关模型DSSMESIMABCNNBIMPM等数据集为LCQMC官方数据","children":[{"title":"text_matching-master","children":[{"title":"README.md <span style='color:#111;'> 582B </span>","children":null,"spread":false},{"title":"data_prepare.py <span style='color:#111;'> 1.84KB </span>","children":null,"spread":false},{"title":"paircnn_ranking","children":[{"title":"PairCNN_Ranking.py <span style='color:#111;'> 6.74KB </span>","children":null,"spread":false},{"title":"result.txt <span style='color:#111;'> 458B </span>","children":null,"spread":false},{"title":"train.py <span style='color:#111;'> 5.93KB </span>","children":null,"spread":false},{"title":"infer.py <span style='color:#111;'> 2.38KB </span>","children":null,"spread":false},{"title":"__pycache__","children":[{"title":"PairCNN_Ranking.cpython-35.pyc <span style='color:#111;'> 4.15KB </span>","children":null,"spread":false}],"spread":true}],"spread":true},{"title":"lstm","children":[{"title":"bi_lstm.py <span style='color:#111;'> 4.34KB </span>","children":null,"spread":false},{"title":"train.py <span style='color:#111;'> 6.32KB </span>","children":null,"spread":false},{"title":"infer.py <span style='color:#111;'> 2.51KB </span>","children":null,"spread":false},{"title":"bi_lstm_attention.py <span style='color:#111;'> 6.00KB </span>","children":null,"spread":false},{"title":"__pycache__","children":[{"title":"bi_lstm.cpython-35.pyc <span style='color:#111;'> 3.59KB </span>","children":null,"spread":false}],"spread":true}],"spread":true},{"title":"config.py <span style='color:#111;'> 351B </span>","children":null,"spread":false},{"title":"语义匹配.pdf <span style='color:#111;'> 1.00MB </span>","children":null,"spread":false},{"title":"save_model","children":[{"title":"lstm","children":[{"title":"vocab.pickle <span style='color:#111;'> 66.43KB </span>","children":null,"spread":false},{"title":"checkpoint <span style='color:#111;'> 199B </span>","children":null,"spread":false}],"spread":true},{"title":"esim","children":[{"title":"vocab.pickle <span style='color:#111;'> 66.99KB </span>","children":null,"spread":false},{"title":"checkpoint <span style='color:#111;'> 199B </span>","children":null,"spread":false}],"spread":true},{"title":"paircnn","children":[{"title":"vocab.pickle <span style='color:#111;'> 66.84KB </span>","children":null,"spread":false},{"title":"checkpoint <span style='color:#111;'> 205B </span>","children":null,"spread":false}],"spread":true},{"title":"abcnn","children":[{"title":"vocab.pickle <span style='color:#111;'> 66.13KB </span>","children":null,"spread":false},{"title":"checkpoint <span style='color:#111;'> 201B </span>","children":null,"spread":false}],"spread":true}],"spread":true},{"title":"esim","children":[{"title":"train.py <span style='color:#111;'> 6.38KB </span>","children":null,"spread":false},{"title":"esim_model.py <span style='color:#111;'> 6.14KB </span>","children":null,"spread":false},{"title":"infer.py <span style='color:#111;'> 2.67KB </span>","children":null,"spread":false},{"title":"__pycache__","children":[{"title":"esim_model.cpython-35.pyc <span style='color:#111;'> 4.59KB </span>","children":null,"spread":false}],"spread":true}],"spread":true},{"title":"__pycache__","children":[{"title":"data_prepare.cpython-35.pyc <span style='color:#111;'> 2.89KB </span>","children":null,"spread":false},{"title":"config.cpython-35.pyc <span style='color:#111;'> 669B </span>","children":null,"spread":false}],"spread":true},{"title":"dssm","children":[{"title":"dssm相关说明.txt <span style='color:#111;'> 968B </span>","children":null,"spread":false},{"title":"dssm_model.py <span style='color:#111;'> 3.51KB </span>","children":null,"spread":false}],"spread":true},{"title":".idea","children":[{"title":"workspace.xml <span style='color:#111;'> 39.96KB </span>","children":null,"spread":false},{"title":"misc.xml <span style='color:#111;'> 203B </span>","children":null,"spread":false},{"title":"modules.xml <span style='color:#111;'> 278B </span>","children":null,"spread":false},{"title":"text_matching.iml <span style='color:#111;'> 586B </span>","children":null,"spread":false}],"spread":true},{"title":"data","children":[{"title":"test.txt <span style='color:#111;'> 758.26KB </span>","children":null,"spread":false},{"title":"dev.txt <span style='color:#111;'> 674.11KB </span>","children":null,"spread":false},{"title":"train.txt <span style='color:#111;'> 15.74MB </span>","children":null,"spread":false}],"spread":true},{"title":"bimpm","children":[{"title":"match_utils.py <span style='color:#111;'> 26.01KB </span>","children":null,"spread":false},{"title":"BiMPM.py <span style='color:#111;'> 13.28KB </span>","children":null,"spread":false},{"title":"layer_utils.py <span style='color:#111;'> 11.86KB </span>","children":null,"spread":false}],"spread":true},{"title":"abcnn","children":[{"title":"train.py <span style='color:#111;'> 5.92KB </span>","children":null,"spread":false},{"title":"abcnn_mdoel.py <span style='color:#111;'> 16.37KB </span>","children":null,"spread":false},{"title":"infer.py <span style='color:#111;'> 2.16KB </span>","children":null,"spread":false},{"title":"abcnn_model_pre.py <span style='color:#111;'> 11.54KB </span>","children":null,"spread":false},{"title":"__pycache__","children":[{"title":"abcnn_mdoel.cpython-35.pyc <span style='color:#111;'> 7.80KB </span>","children":null,"spread":false}],"spread":false}],"spread":false},{"title":"papers","children":[{"title":"Learning deep structured semantic models for web search using clickthrough.pdf <span style='color:#111;'> 434.92KB </span>","children":null,"spread":false},{"title":"Bilateral Multi-Perspective Matching for Natural Language Sentences.pdf <span style='color:#111;'> 359.06KB </span>","children":null,"spread":false},{"title":"Learning to Rank Short Text Pairs with Convolutional Deep Neural Networks.pdf <span style='color:#111;'> 654.09KB </span>","children":null,"spread":false},{"title":"Enhanced LSTM for Natural Language Inference.pdf <span style='color:#111;'> 984.65KB </span>","children":null,"spread":false},{"title":"MultiwayAttentionNetworksforModelingSentencePairs.pdf <span style='color:#111;'> 199.36KB </span>","children":null,"spread":false},{"title":"Attention-Based Convolutional Neural Network for Modeling Sentence Pairs.pdf <span style='color:#111;'> 572.23KB </span>","children":null,"spread":false}],"spread":false}],"spread":false}],"spread":true}]

评论信息

免责申明

【只为小站】的资源来自网友分享,仅供学习研究,请务必在下载后24小时内给予删除,不得用于其他任何用途,否则后果自负。基于互联网的特殊性,【只为小站】 无法对用户传输的作品、信息、内容的权属或合法性、合规性、真实性、科学性、完整权、有效性等进行实质审查;无论 【只为小站】 经营者是否已进行审查,用户均应自行承担因其传输的作品、信息、内容而可能或已经产生的侵权或权属纠纷等法律责任。
本站所有资源不代表本站的观点或立场,基于网友分享,根据中国法律《信息网络传播权保护条例》第二十二条之规定,若资源存在侵权或相关问题请联系本站客服人员,zhiweidada#qq.com,请把#换成@,本站将给予最大的支持与配合,做到及时反馈和处理。关于更多版权及免责申明参见 版权及免责申明