From b93182f69e20c5515a658bf7177abd719f445f1b Mon Sep 17 00:00:00 2001
From: Thomas Simonini <simonini_thomas@outlook.fr>
Date: Fri, 4 Nov 2022 09:11:34 +0100
Subject: [PATCH] Create cleanrl.md

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+---
+title: 'Welcome CleanRL to the Hugging Face Hub 🤗'
+thumbnail: /blog/assets/114_cleanrl/thumbnail.png
+---
+
+<h1>
+    Welcome CleanRL to the Hugging Face Hub 🤗
+</h1>
+
+<div class="blog-metadata">
+    <small>Published November 27, 2022.</small>
+    <a target="_blank" class="btn no-underline text-sm mb-5 font-sans" href="https://github.com/huggingface/blog/blob/main/sample-factory.md">
+        Update on GitHub
+    </a>
+</div>
+
+<div class="author-card">
+    <a href="/ThomasSimonini"> 
+        <img class="avatar avatar-user" src="https://aeiljuispo.cloudimg.io/v7/https://s3.amazonaws.com/moonup/production/uploads/1632748593235-60cae820b1c79a3e4b436664.jpeg?w=200&h=200&f=face" title="Gravatar">
+        <div class="bfc">
+            <code>ThomasSimonini</code>
+            <span class="fullname">Thomas Simonini</span>
+        </div>
+    </a>
+</div>
+
+At Hugging Face, we are contributing to the ecosystem for Deep Reinforcement Learning researchers and enthusiasts. That’s why we’re happy to announce that we integrated [CleanRL](https://github.com/vwxyzjn/cleanrl) to the Hugging Face Hub.
+
+[CleanRL](https://github.com/vwxyzjn/cleanrl) is a Deep Reinforcement Learning library that provides high-quality single-file implementation with research-friendly features.
+With this integration, you can now host your saved models 💾 and load powerful models from the community.
+
+ADD VIDEO CleanRL
+
+In this article, we’re going to show how you can do it. But if you want to follow with a tutorial, we wrote one where you'll learn:
+- How to train a Deep Reinforcement Learning lander agent to land correctly on the Moon 🌕 
+- How to upload it to the Hub 🚀
+
+![gif](assets/47_sb3/lunarlander.gif)
+
+- How to download and use a saved model from the Hub that CHOOSE ENVIRONMENT
+
+👉 [The tutorial]() ADD LINK
+
+Sounds exciting? Let's get started!
+
+- [Install the library]()
+- [Exploring CleanRL in the Hub]()
+- [Uploading models to the Hub]()
+- [Loading models from the Hub]()
+
+TODO finish the table des matières when titles are chosen
+
+
+## What's next?
+In the coming weeks and months, we plan on supporting other tools from the ecosystem:
+
+- Integrating [Sample Factory](https://github.com/alex-petrenko/sample-factory) to the Hub.
+- Launching the Beta of [Simulate](https://github.com/huggingface/simulate), a library for easily creating and sharing simulation environments for intelligent agents
+- Expanding our repository of Decision Transformer models with models trained or finetuned in an online setting [1]
+
+The best way to keep in touch is to **[join our discord server](https://discord.gg/YRAq8fMnUG)** to exchange with us and with the community.
+
+Finally, we would like to thank the ADD COSTA THANKS
+
+### Would you like to integrate your library to the Hub?
+
+This integration is possible thanks to the [`huggingface_hub`](https://github.com/huggingface/huggingface_hub) library which has all our widgets and the API for all our supported libraries. If you would like to integrate your library to the Hub, we have a [guide](https://huggingface.co/docs/hub/models-adding-libraries) for you!
+
+## References
+[1] Zheng, Qinqing and Zhang, Amy and Grover, Aditya “Online Decision Transformer” (arXiv preprint, 2022)