Merge pull request #12 from samvelyan/samvelyan/readme

Added the banners back

Author: samvelyan

README.md

@@ -2,11 +2,18 @@
  <img width="80%" src="https://raw.githubusercontent.com/facebookresearch/minihack/main/docs/imgs/minihack.png" />
 </p>
 
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+>
 
 <p align="center">
-  <b>Please find MiniHack at its new home at <a href="https://github.com/samvelyan/minihack">github.com/samvelyan/minihack</a></b>
-</p>
+  <a href="https://pypi.python.org/pypi/minihack/"><img src="https://img.shields.io/pypi/v/minihack.svg" /></a>
+  <a href="https://opensource.org/licenses/Apache-2.0"><img src="https://img.shields.io/badge/License-Apache%202.0-blue.svg" /></a>
+  <a href="https://minihack.readthedocs.io/en/latest/?badge=latest"><img src="https://readthedocs.org/projects/minihack/badge/?version=latest" /></a>
+  <a href="https://pepy.tech/project/minihack"><img src="https://static.pepy.tech/personalized-badge/minihack?period=total&units=international_system&left_color=black&right_color=red&left_text=Downloads" /></a>
+  <a href="https://github.com/facebookresearch/minihack/actions/workflows/test_and_deploy.yml"><img src="https://github.com/facebookresearch/minihack/actions/workflows/test_and_deploy.yml/badge.svg?branch=main" /></a>
+  <a href="https://arxiv.org/abs/2109.13202"><img src="https://img.shields.io/badge/arXiv-2109.13202-b31b1b.svg"/></a>
+ </p>
+
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 MiniHack is a sandbox framework for easily designing rich and diverse environments for Reinforcement Learning (RL).
 Based on the game of [NetHack](https://en.wikipedia.org/wiki/NetHack), MiniHack uses the [NetHack Learning Environment (NLE)](https://github.com/heiner/nle) to communicate with the game and to provide a convenient interface for customly created RL training and test environments of varying complexity.