bertsum-chinese | chinese bertsum ; bertsum
kandi X-RAY | bertsum-chinese Summary
kandi X-RAY | bertsum-chinese Summary
bertsum-chinese is a Python library. bertsum-chinese has no vulnerabilities and it has low support. However bertsum-chinese has 1 bugs and it build file is not available. You can download it from GitHub.
chinese bertsum ; bertsum 抽取式模型中文版本;给出案例数据、全代码注释;下载即可训练、预测、学习
chinese bertsum ; bertsum 抽取式模型中文版本;给出案例数据、全代码注释;下载即可训练、预测、学习
Support
Quality
Security
License
Reuse
Support
bertsum-chinese has a low active ecosystem.
It has 119 star(s) with 21 fork(s). There are 2 watchers for this library.
It had no major release in the last 6 months.
There are 1 open issues and 7 have been closed. On average issues are closed in 125 days. There are no pull requests.
It has a neutral sentiment in the developer community.
The latest version of bertsum-chinese is current.
Quality
bertsum-chinese has 1 bugs (0 blocker, 0 critical, 1 major, 0 minor) and 44 code smells.
Security
bertsum-chinese has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
bertsum-chinese code analysis shows 0 unresolved vulnerabilities.
There are 1 security hotspots that need review.
License
bertsum-chinese 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
bertsum-chinese releases are not available. You will need to build from source code and install.
bertsum-chinese has no build file. You will be need to create the build yourself to build the component from source.
It has 1947 lines of code, 144 functions and 35 files.
It has medium code complexity. Code complexity directly impacts maintainability of the code.
Top functions reviewed by kandi - BETA
kandi has reviewed bertsum-chinese and discovered the below as its top functions. This is intended to give you an instant insight into bertsum-chinese implemented functionality, and help decide if they suit your requirements.
- Save data array to json file
- Given a list of key_sents and key_sents return the label associated with that key
- Split a sentence into tokens
- Convert documents to json format
- Return a summary of the model
- Predict a document
- Split a long document
- Predict a given document
- Train the model
- Calculate the loss function
- Load a dataset
- Train the optimizer
- Split a docstring into a list
- Strip whitespace characters
- Replace whitespace in text
- Build an optimizer
- Set parameters
- Returns whether the user can use GPU
- Format data to BertData
- Preprocess src
- Run test
- Evaluate the model
- Applies statistics to the data
- Get input data iterator
- Load a model from file
- Return the number of sentsounts
Get all kandi verified functions for this library.
bertsum-chinese Key Features
No Key Features are available at this moment for bertsum-chinese.
bertsum-chinese Examples and Code Snippets
No Code Snippets are available at this moment for bertsum-chinese.
Community Discussions
No Community Discussions are available at this moment for bertsum-chinese.Refer to stack overflow page for discussions.
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install bertsum-chinese
You can download it from GitHub.
You can use bertsum-chinese 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.
You can use bertsum-chinese 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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