Add metadata, link to code

This PR adds relevant metadata to improve model discoverability. It also includes a concise model description and links to the paper and code.

README.md

@@ -1,3 +1,11 @@
----
-license: apache-2.0
----
+---
+license: apache-2.0
+pipeline_tag: question-answering
+library_name: transformers
+---
+
+This repository contains the model described in the paper [SimpleRL-Zoo: Investigating and Taming Zero Reinforcement Learning for Open Base Models in the Wild](https://arxiv.org/abs/2503.18892).
+
+This model has been trained with a simple reinforcement learning (RL) recipe to improve reasoning abilities.  Training starts from base models and uses rule-based rewards and the GSM8K/Math datasets.  This approach has been successfully applied to diverse base models with limited data (8K examples), achieving significant accuracy gains ranging from 10 to more than 20 absolute points.
+
+Code: https://github.com/hkust-nlp/simpleRL-reason/tree/v1