Metadata-Version: 2.1
Name: genbase
Version: 0.1.0
Summary: Generation base dependency
Home-page: https://git.science.uu.nl/m.j.robeer/genbase
Author: Marcel Robeer
Author-email: m.j.robeer@uu.nl
License: GNU LGPL v3
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Programming Language :: Python
Classifier: License :: OSI Approved :: GNU Lesser General Public License v3 or later (LGPLv3+)
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Requires-Python: >=3.8
Description-Content-Type: text/markdown
License-File: LICENSE

# Generation base dependency

[![PyPI](https://img.shields.io/pypi/v/genbase)](https://pypi.org/project/genbase/)
[![Python_version](https://img.shields.io/badge/python-3.8%20%7C%203.9%20%7C%203.10-blue)](https://pypi.org/project/genbase/)
[![Build_passing](https://img.shields.io/badge/build-passing-brightgreen)](https://git.science.uu.nl/m.j.robeer/genbase/-/pipelines)
[![License](https://img.shields.io/pypi/l/genbase)](https://www.gnu.org/licenses/lgpl-3.0.en.html)

&copy; Marcel Robeer, 2021

## Installation
| Method | Instructions |
|--------|--------------|
| `pip` | Install from [PyPI](https://pypi.org/project/text-explainability/) via `pip3 install genbase`. |
| Local | Clone this repository and install via `pip3 install -e .` or locally run `python3 setup.py install`.

## Releases
`text_explainability` is officially released through [PyPI](https://pypi.org/project/text-explainability/).

See [CHANGELOG.md](CHANGELOG.md) for a full overview of the changes for each version.

## Packages using `genbase`

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<a href="https://marcelrobeer.github.io/text_explainability/" target="_blank"><img src="https://git.science.uu.nl/m.j.robeer/text_explainability/-/raw/main/img/TextLogo-Logo large.png" alt="T_xt explainability logo" width="200px"></a><p>`text_explainability` provides a generic architecture from which well-known state-of-the-art explainability approaches for text can be composed. This modular architecture allows components to be swapped out and combined, to quickly develop new types of explainability approaches for (natural language) text, or to improve a plethora of approaches by improving a single module. The `explainability` package is available through [PyPI](https://pypi.org/project/text-explainability/) and fully documented at [https://marcelrobeer.github.io/text_explainability/](https://marcelrobeer.github.io/text_explainability/).</p>

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<a href="https://marcelrobeer.github.io/text_sensitivity/" target="_blank"><img src="https://git.science.uu.nl/m.j.robeer/text_sensitivity/-/raw/main/img/TextLogo-Logo_large_sensitivity.png" alt="T_xt sensitivity logo" width="200px"></a><p>`text_explainability` can be extended to also perform _sensitivity testing_, checking for machine learning model robustness and fairness. The `text_sensitivity` package is available through [PyPI](https://pypi.org/project/text-sensitivity/) and fully documented at [https://marcelrobeer.github.io/text_sensitivity/](https://marcelrobeer.github.io/text_sensitivity/).</p>

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