nn-convert | A set of scripts for conversions between pre-trained models

by macenpav Python Version: Current License: MIT

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

kandi X-RAY | nn-convert Summary

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

A set of scripts for conversions between pre-trained models - caffe, tf, tflite.

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Support

nn-convert 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.

nn-convert has no issues reported. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of nn-convert is current.

Quality

nn-convert has no bugs reported.

Security

nn-convert has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

nn-convert 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

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

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

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nn-convert Key Features

No Key Features are available at this moment for nn-convert.

nn-convert Examples and Code Snippets

No Code Snippets are available at this moment for nn-convert.

Community Discussions

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

Vulnerabilities

No vulnerabilities reported

Install nn-convert

You can download it from GitHub.
You can use nn-convert 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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