lb-wavenet | Another TensorFlow implementation of WaveNet

by hrbigelow Python Version: Current License: No License

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

kandi X-RAY | lb-wavenet Summary

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

Another TensorFlow implementation of WaveNet, using a lookback technique for efficient training

Support

Quality

Security

License

Reuse

Support

lb-wavenet 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.

lb-wavenet has no issues reported. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of lb-wavenet is current.

Quality

lb-wavenet has no bugs reported.

Security

lb-wavenet has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

lb-wavenet 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

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

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

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lb-wavenet Key Features

No Key Features are available at this moment for lb-wavenet.

lb-wavenet Examples and Code Snippets

No Code Snippets are available at this moment for lb-wavenet.

Community Discussions

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

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

Vulnerabilities

No vulnerabilities reported

Install lb-wavenet

You can download it from GitHub.
You can use lb-wavenet 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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