# NitroGen **Repository Path**: xiaolang1/NitroGen ## Basic Information - **Project Name**: NitroGen - **Description**: No description available - **Primary Language**: Unknown - **License**: Not specified - **Default Branch**: main - **Homepage**: None - **GVP Project**: No ## Statistics - **Stars**: 0 - **Forks**: 0 - **Created**: 2025-12-22 - **Last Updated**: 2025-12-22 ## Categories & Tags **Categories**: Uncategorized **Tags**: None ## README

Website | Model | Dataset | Paper

# 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 ``` Then, run the agent on the game of your choice: ```bash python scripts/play.py --process '.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`. **Disclaimer**: This project is strictly for research purposes and is not an official NVIDIA product.