nlpcc2017_news_headline_categorization | NLPCC2017示例代码以及数据描述

by FudanNLP Python Version: Current License: No License

X-Ray Key Features Code Snippets Community Discussions Vulnerabilities Install Support

kandi X-RAY | nlpcc2017_news_headline_categorization Summary

nlpcc2017_news_headline_categorization is a Python library. nlpcc2017_news_headline_categorization has no bugs, it has no vulnerabilities and it has low support. However nlpcc2017_news_headline_categorization build file is not available. You can download it from GitHub.

NLPCC2017示例代码以及数据描述

Support

Quality

Security

License

Reuse

Support

nlpcc2017_news_headline_categorization has a low active ecosystem.

It has 114 star(s) with 55 fork(s). There are 12 watchers for this library.

It had no major release in the last 6 months.

There are 7 open issues and 4 have been closed. On average issues are closed in 5 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of nlpcc2017_news_headline_categorization is current.

Quality

nlpcc2017_news_headline_categorization has 0 bugs and 0 code smells.

Security

nlpcc2017_news_headline_categorization has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

nlpcc2017_news_headline_categorization code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

nlpcc2017_news_headline_categorization does not have a standard license declared.

Check the repository for any license declaration and review the terms closely.

Without a license, all rights are reserved, and you cannot use the library in your applications.

Reuse

nlpcc2017_news_headline_categorization releases are not available. You will need to build from source code and install.

nlpcc2017_news_headline_categorization has no build file. You will be need to create the build yourself to build the component from source.

Installation instructions are not available. Examples and code snippets are available.

nlpcc2017_news_headline_categorization saves you 528 person hours of effort in developing the same functionality from scratch.

It has 1237 lines of code, 105 functions and 5 files.

It has high code complexity. Code complexity directly impacts maintainability of the code.

Top functions reviewed by kandi - BETA

kandi has reviewed nlpcc2017_news_headline_categorization and discovered the below as its top functions. This is intended to give you an instant insight into nlpcc2017_news_headline_categorization implemented functionality, and help decide if they suit your requirements.

Self - attention
Compute a linear tensor
Linear linear operator
Creates a mask from input_tensor
Compute the softmax loss
Calculate the weighted average

Get all kandi verified functions for this library.

nlpcc2017_news_headline_categorization Key Features

No Key Features are available at this moment for nlpcc2017_news_headline_categorization.

nlpcc2017_news_headline_categorization Examples and Code Snippets

No Code Snippets are available at this moment for nlpcc2017_news_headline_categorization.

Community Discussions

No Community Discussions are available at this moment for nlpcc2017_news_headline_categorization.Refer to stack overflow page for discussions.

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install nlpcc2017_news_headline_categorization

You can download it from GitHub.
You can use nlpcc2017_news_headline_categorization like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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