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+<img src="assets/github_banner.gif" width="100%" />
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+<div align="center">
+  <p style="font-size: 1.2em;">
+    <a href="https://nitrogen.minedojo.org/"><strong>Website</strong></a> | 
+    <a href="https://huggingface.co/nvidia/NitroGen"><strong>Model</strong></a> |
+    <a href="https://huggingface.co/datasets/nvidia/NitroGen"><strong>Dataset</strong></a> |
+    <a href="https://nitrogen.minedojo.org/assets/documents/nitrogen.pdf"><strong>Paper</strong></a>
+  </p>
+</div>
+
+
+# NitroGen
+
+NitroGen is an open foundation model for generalist gaming agents. This multi-game model takes pixel input and predicts gamepad actions.
+
+NitroGen is trained through behavior cloning on the largest video-action gameplay dataset, assembled exclusively from internet videos. It can be adapted via post-training to unseen games.
+
+# Installation
+
+## Prerequisites
+
+We **do not distribute game environments**, you must use your own copies of the games. This repository only supports running the agent on **Windows games**. You can serve the model from a Linux machine for inference, but the game ultimately has to run on Windows. We have tested on Windows 11 with Python ≥ 3.12.
+
+## Setup
+
+Install this repo:
+```bash
+git clone https://github.com/MineDojo/NitroGen.git
+cd NitroGen
+pip install -e .
+```
+
+Download NitroGen checkpoint from [HuggingFace](https://huggingface.co/nvidia/NitroGen):
+```bash
+hf download nvidia/NitroGen ng.pt
+```
+
+# Getting Started
+
+First, start an inference server for the model:
+```bash
+python scripts/serve.py <path_to_ng.pt>  
+```
+
+Then, run the agent on the game of your choice:
+```bash
+python scripts/play.py --process '<game_executable_name>.exe'
+```
+
+The `--process` parameter must be the exact executable name of the game you want to play. You can find it by right-clicking on the game process in Windows Task Manager (Ctrl+Shift+Esc), and selecting `Properties`. The process name should be in the `General` tab and end with `.exe`.
+
+<!-- TODO # Paper and Citation
+
+If you find our work useful, please consider citing us!
+
+```bibtex
+@article{,
+  title   = {},
+  author  = {},
+  year    = {},
+  journal = {}
+}
+``` -->
+
+**Disclaimer**: This project is strictly for research purposes and is not an official NVIDIA product.