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Add more version badges and bibtex section to README.md

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@ -7,6 +7,8 @@ prototype-based machine learning algorithms.
[![PyPI version](https://badge.fury.io/py/prototorch.svg)](https://badge.fury.io/py/prototorch) [![PyPI version](https://badge.fury.io/py/prototorch.svg)](https://badge.fury.io/py/prototorch)
![Tests](https://github.com/si-cim/prototorch/workflows/Tests/badge.svg) ![Tests](https://github.com/si-cim/prototorch/workflows/Tests/badge.svg)
[![codecov](https://codecov.io/gh/si-cim/prototorch/branch/master/graph/badge.svg)](https://codecov.io/gh/si-cim/prototorch) [![codecov](https://codecov.io/gh/si-cim/prototorch/branch/master/graph/badge.svg)](https://codecov.io/gh/si-cim/prototorch)
[![Downloads](https://pepy.tech/badge/prototorch)](https://pepy.tech/project/prototorch)
[![GitHub license](https://img.shields.io/github/license/si-cim/prototorch)](https://github.com/si-cim/prototorch/blob/master/LICENSE)
## Description ## Description
@ -49,3 +51,16 @@ API, with more algorithms and techniques coming soon. If you would simply like
to be able to use those algorithms to train large ML models on a GPU, ProtoTorch to be able to use those algorithms to train large ML models on a GPU, ProtoTorch
lets you do this without requiring a black-belt in high-performance Tensor lets you do this without requiring a black-belt in high-performance Tensor
computation. computation.
## Bibtex
If you would like to cite the package, please use this:
```bibtex
@misc{Ravichandran2020,
author = {Ravichandran, J},
title = {ProtoTorch},
year = {2020},
publisher = {GitHub},
journal = {GitHub repository},
howpublished = {\url{https://github.com/si-cim/prototorch}}
}