N-gram_NLP_Model | gram language model to generate new text

by philipp-kurz Python Version: Current License: No License

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kandi X-RAY | N-gram_NLP_Model Summary

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

N-gram language model to generate new text when trained with corpora of text. Written as part of HW4 for class CS188 - "Introduction to Artificial Intelligence" at UC Berkeley during the Spring 2020 semester.

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N-gram_NLP_Model has a low active ecosystem.

It has 0 star(s) with 0 fork(s). There are 1 watchers for this library.

It had no major release in the last 6 months.

N-gram_NLP_Model has no issues reported. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of N-gram_NLP_Model is current.

Quality

N-gram_NLP_Model has no bugs reported.

Security

N-gram_NLP_Model has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

N-gram_NLP_Model 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.

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N-gram_NLP_Model releases are not available. You will need to build from source code and install.

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

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N-gram_NLP_Model Key Features

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N-gram_NLP_Model Examples and Code Snippets

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Vulnerabilities

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Install N-gram_NLP_Model

You can download it from GitHub.
You can use N-gram_NLP_Model 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.

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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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