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Mainly you could copy the README.md here. However, you should be careful with:

  • The banner section is different
  • Link to assets (handling dark mode is different between GitHub and the documentation)
  • Relative links


Libname is a Python toolkit dedicated to making people happy and fun.
Explore Libname docs »

📚 Table of contents

🔥 Tutorials

We propose some tutorials to get familiar with the library and its API:

You do not necessarily need to register the notebooks on GitHub. Notebooks can be hosted on a specific drive.

🚀 Quick Start

Libname requires some stuff and several libraries including Numpy. Installation can be done using Pypi:

pip install libname

Now that Libname is installed, here are some basic examples of what you can do with the available modules.

Let's start with a simple example:

from libname.fake import hello_world

hello_world()

Make addition

In order to add a to b you can use:

from libname.fake import addition

a = 1
b = 2
c = addition(a, b)

📦 What's Included

A list or table of methods available

👍 Contributing

Feel free to propose your ideas or come and contribute with us on the Libname toolbox! We have a specific document where we describe in a simple way how to make your first pull request: just here.

👀 See Also

This library is one approach of many...

Other tools to explain your model include:

More from the DEEL project:

  • Xplique a Python library exclusively dedicated to explaining neural networks.
  • deel-lip a Python library for training k-Lipschitz neural networks on TF.
  • Influenciae Python toolkit dedicated to computing influence values for the discovery of potentially problematic samples in a dataset.
  • deel-torchlip a Python library for training k-Lipschitz neural networks on PyTorch.
  • DEEL White paper a summary of the DEEL team on the challenges of certifiable AI and the role of data quality, representativity and explainability for this purpose.

🙏 Acknowledgments

DEEL Logo DEEL Logo This project received funding from the French ”Investing for the Future – PIA3” program within the Artificial and Natural Intelligence Toulouse Institute (ANITI). The authors gratefully acknowledge the support of the DEEL project.

👨‍🎓 Creators

If you want to highlight the main contributors

🗞️ Citation

If you use Libname as part of your workflow in a scientific publication, please consider citing 🗞️ our paper:

@article{rickroll,
  title={Rickrolling},
  author={Some Internet Trolls},
  journal={Best Memes},
  year={ND}
}

📝 License

The package is released under MIT license.