TextSum | Preparing a dataset for TensorFlow text summarization | Machine Learning library

by surmenok Python Version: Current License: MIT

X-Ray Key Features Code Snippets Community Discussions(1)Vulnerabilities Install Support

kandi X-RAY | TextSum Summary

TextSum is a Python library typically used in Artificial Intelligence, Machine Learning, Deep Learning, Tensorflow applications. TextSum has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. However TextSum build file is not available. You can download it from GitHub.

Preparing a dataset for TensorFlow text summarization (TextSum) model.

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Quality

Security

License

Reuse

Support

TextSum has a low active ecosystem.

It has 140 star(s) with 62 fork(s). There are 12 watchers for this library.

It had no major release in the last 6 months.

There are 2 open issues and 0 have been closed. On average issues are closed in 1048 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of TextSum is current.

Quality

TextSum has 0 bugs and 1 code smells.

Security

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

TextSum code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

TextSum is licensed under the MIT License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

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

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

TextSum saves you 30 person hours of effort in developing the same functionality from scratch.

It has 81 lines of code, 5 functions and 1 files.

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

Top functions reviewed by kandi - BETA

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

Write text files to a vocabulary
Returns a list of filenames from input_directories
Convert input files to binary

Get all kandi verified functions for this library.

TextSum Key Features

No Key Features are available at this moment for TextSum.

TextSum Examples and Code Snippets

No Code Snippets are available at this moment for TextSum.

Community Discussions

Trending Discussions on TextSum

Dependency to numpy cannot be resolved when installing requirements.txt in Azure Functions

QUESTION

Dependency to numpy cannot be resolved when installing requirements.txt in Azure Functions

Asked 2021-Feb-01 at 03:35

My azure function is using python module pywavelets which requires dependency to numpy. Here is my requirements.txt

...

ANSWER

Answered 2021-Feb-01 at 03:35

I test in my side with same modules as yours in my requirements.txt and run the function with Ctrl + F5. It shows same error message as you mentioned.

It seems there are some conflicts of the two modules(in the versions which you specified in your requirements.txt). To solve this problem, just remove the version of the two modules in requirements.txt. Below is my requirements.txt:

If we do not specify the version, it will install the latest version automatically. In my function app, it intalls numpy 1.20.0 and PyWavelets 1.1.1, and the function runs success when I use Ctrl + F5.

Source https://stackoverflow.com/questions/65964789

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

Vulnerabilities

No vulnerabilities reported

Install TextSum

You can download it from GitHub.
You can use TextSum 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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