OpenNRE:神经关系提取(NRE)的开源软件包-Open source

上传者: 42116650 | 上传时间: 2021-07-19 10:42:44 | 文件大小: 47KB | 文件类型: ZIP
OpenNRE 我们有一个DEMO网站( )。 试试看! OpenNRE是一个开源且可扩展的工具包,它提供了用于实现关系提取模型的统一框架。 该软件包是为以下人群设计的: 关系提取的新知识:我们提供了手工教程和详细文档,它们不仅使您能够使用关系提取工具,而且还可以帮助您更好地了解该领域的研究进展。 开发人员:我们易于使用的界面和高性能的实现可以加速您在实际应用程序中的部署。 此外,我们提供了几种预训练的模型,这些模型无需任何培训即可投入生产。 研究人员:借助我们的模块化设计,各种任务设置和度量工具,您只需进行少量修改就可以轻松地对自己的模型进行实验。 我们还为关系提取的不同设置提供了几种最常用的基准。 任何需要提交NLP作业以打动他们的教授的人:借助最先进的模型,我们的软件包可以绝对帮助您在同学中脱颖而出! 该软件包主要由,,,,,贡献。 什么是关系提取 关系提取是一种自然

文件下载

资源详情

[{"title":"( 46 个子文件 47KB ) OpenNRE:神经关系提取(NRE)的开源软件包-Open source","children":[{"title":"OpenNRE-master","children":[{"title":"benchmark","children":[{"title":"download_nyt10.sh <span style='color:#111;'> 304B </span>","children":null,"spread":false},{"title":"download_wiki80.sh <span style='color:#111;'> 313B </span>","children":null,"spread":false},{"title":"download_fewrel.sh <span style='color:#111;'> 425B </span>","children":null,"spread":false},{"title":"download_semeval.sh <span style='color:#111;'> 425B </span>","children":null,"spread":false}],"spread":true},{"title":"example","children":[{"title":"train_supervised_bert.py <span style='color:#111;'> 4.59KB </span>","children":null,"spread":false},{"title":"train_bag_pcnn_att.py <span style='color:#111;'> 4.77KB </span>","children":null,"spread":false},{"title":"train_supervised_cnn.py <span style='color:#111;'> 4.28KB </span>","children":null,"spread":false}],"spread":true},{"title":"pretrain","children":[{"title":"download_glove.sh <span style='color:#111;'> 219B </span>","children":null,"spread":false},{"title":"download_bert.sh <span style='color:#111;'> 376B </span>","children":null,"spread":false}],"spread":true},{"title":"tests","children":[{"title":"test_inference.py <span style='color:#111;'> 550B </span>","children":null,"spread":false}],"spread":true},{"title":"LICENSE <span style='color:#111;'> 1.04KB </span>","children":null,"spread":false},{"title":"requirements.txt <span style='color:#111;'> 93B </span>","children":null,"spread":false},{"title":"opennre","children":[{"title":"tokenization","children":[{"title":"utils.py <span style='color:#111;'> 8.43KB </span>","children":null,"spread":false},{"title":"bert_tokenizer.py <span style='color:#111;'> 2.14KB </span>","children":null,"spread":false},{"title":"word_piece_tokenizer.py <span style='color:#111;'> 3.79KB </span>","children":null,"spread":false},{"title":"basic_tokenizer.py <span style='color:#111;'> 2.57KB </span>","children":null,"spread":false},{"title":"__init__.py <span style='color:#111;'> 752B </span>","children":null,"spread":false},{"title":"word_tokenizer.py <span style='color:#111;'> 2.65KB </span>","children":null,"spread":false}],"spread":true},{"title":"model","children":[{"title":"bag_attention.py <span style='color:#111;'> 6.23KB </span>","children":null,"spread":false},{"title":"softmax_nn.py <span style='color:#111;'> 1.40KB </span>","children":null,"spread":false},{"title":"bag_average.py <span style='color:#111;'> 3.38KB </span>","children":null,"spread":false},{"title":"__init__.py <span style='color:#111;'> 387B </span>","children":null,"spread":false},{"title":"base_model.py <span style='color:#111;'> 1.70KB </span>","children":null,"spread":false}],"spread":true},{"title":"framework","children":[{"title":"utils.py <span style='color:#111;'> 721B </span>","children":null,"spread":false},{"title":"data_loader.py <span style='color:#111;'> 9.95KB </span>","children":null,"spread":false},{"title":"__init__.py <span style='color:#111;'> 393B </span>","children":null,"spread":false},{"title":"bag_re.py <span style='color:#111;'> 6.66KB </span>","children":null,"spread":false},{"title":"sentence_re.py <span style='color:#111;'> 6.26KB </span>","children":null,"spread":false}],"spread":true},{"title":"__init__.py <span style='color:#111;'> 625B </span>","children":null,"spread":false},{"title":"module","children":[{"title":"pool","children":[{"title":"__init__.py <span style='color:#111;'> 213B </span>","children":null,"spread":false},{"title":"max_pool.py <span style='color:#111;'> 2.22KB </span>","children":null,"spread":false},{"title":"avg_pool.py <span style='color:#111;'> 1.77KB </span>","children":null,"spread":false}],"spread":true},{"title":"nn","children":[{"title":"cnn.py <span style='color:#111;'> 1.03KB </span>","children":null,"spread":false},{"title":"rnn.py <span style='color:#111;'> 1.29KB </span>","children":null,"spread":false},{"title":"__init__.py <span style='color:#111;'> 223B </span>","children":null,"spread":false},{"title":"lstm.py <span style='color:#111;'> 1.30KB </span>","children":null,"spread":false}],"spread":false},{"title":"__init__.py <span style='color:#111;'> 109B </span>","children":null,"spread":false}],"spread":true},{"title":"encoder","children":[{"title":"bert_encoder.py <span style='color:#111;'> 8.22KB </span>","children":null,"spread":false},{"title":"base_encoder.py <span style='color:#111;'> 5.91KB </span>","children":null,"spread":false},{"title":"cnn_encoder.py <span style='color:#111;'> 2.50KB </span>","children":null,"spread":false},{"title":"__init__.py <span style='color:#111;'> 335B </span>","children":null,"spread":false},{"title":"pcnn_encoder.py <span style='color:#111;'> 6.82KB </span>","children":null,"spread":false}],"spread":true},{"title":"pretrain.py <span style='color:#111;'> 9.32KB </span>","children":null,"spread":false}],"spread":true},{"title":"setup.py <span style='color:#111;'> 582B </span>","children":null,"spread":false},{"title":".gitignore <span style='color:#111;'> 1.47KB </span>","children":null,"spread":false},{"title":"README.md <span style='color:#111;'> 5.68KB </span>","children":null,"spread":false}],"spread":true}],"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