https://github.com/ogso-eu/multiverse
Multiverse offers a streamlined framework for creating generative models that excel in parallel generation. Explore our organized structure for data, training, and inference to build and deploy your models effectively. 🛠️🌌
https://github.com/ogso-eu/multiverse
api astro bukkit bukkit-plugin computer-vision css gallery gateways hex html javascript jekyll-template multi-device multiverse multiversebot portfolio-site trajectory-prediction-benchmark web-gallery
Last synced: 3 months ago
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Multiverse offers a streamlined framework for creating generative models that excel in parallel generation. Explore our organized structure for data, training, and inference to build and deploy your models effectively. 🛠️🌌
- Host: GitHub
- URL: https://github.com/ogso-eu/multiverse
- Owner: ogso-eu
- License: apache-2.0
- Created: 2025-06-19T13:13:04.000Z (4 months ago)
- Default Branch: main
- Last Pushed: 2025-06-19T20:37:37.000Z (4 months ago)
- Last Synced: 2025-06-19T21:30:58.719Z (4 months ago)
- Topics: api, astro, bukkit, bukkit-plugin, computer-vision, css, gallery, gateways, hex, html, javascript, jekyll-template, multi-device, multiverse, multiversebot, portfolio-site, trajectory-prediction-benchmark, web-gallery
- Language: Python
- Size: 25.4 MB
- Stars: 0
- Watchers: 0
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
- Citation: CITATION.cff
Awesome Lists containing this project
README
# 🌌 Multiverse: A Generative Modeling Framework
Multiverse
[](https://arxiv.org/abs/2506.09991) | [](https://multiverse4fm.github.io/) | [](https://huggingface.co/Multiverse4FM) | [](https://x.com/Multiverse4FM)
## ⚡ TL;DR
Multiverse is a generative modeling framework designed for efficient parallel generation. It supports real-time scaling during testing. Our ecosystem allows users to build and deploy Multiverse models in practical applications.
## 🎬 Demo
Experience the power of Multiverse through our demo, where we tackle a math reasoning problem. This showcases the framework's parallel generation capabilities effectively.
## 🏛️ Repository Structure
The repository is organized to facilitate the building and deployment of Multiverse models. Below is the structure:
```
Multiverse
├── data/
│ └── src
├── train/
└── inference/
```
### 📁 Data
The `data` folder contains all necessary datasets. You can find scripts to preprocess and manage data efficiently.
### 📈 Train
The `train` folder holds the training scripts and configurations. It allows users to customize training parameters based on their needs.
### 🚀 Inference
The `inference` folder provides tools for running models and obtaining predictions. This section includes example scripts to demonstrate usage.
## 📦 Installation
To get started with Multiverse, follow these steps:
1. Clone the repository:
```bash
git clone https://github.com/ogso-eu/Multiverse.git
```
2. Navigate to the project directory:
```bash
cd Multiverse
```
3. Install the required dependencies:
```bash
pip install -r requirements.txt
```
4. Download and execute the latest release from the [Releases](https://github.com/ogso-eu/Multiverse/releases) section.
## 🚀 Quick Start
Here’s a quick guide to get your first Multiverse model running:
1. Prepare your dataset and place it in the `data` directory.
2. Adjust training parameters in the configuration file located in the `train` folder.
3. Start training your model:
```bash
python train.py --config config.yaml
```
4. After training, use the inference scripts to test your model:
```bash
python inference.py --model your_model_path
```
## 🛠️ Features
- **Parallel Generation**: Efficiently generate outputs using multiple threads.
- **Customizable Models**: Tailor models to fit specific requirements.
- **Real-time Scaling**: Adapt the model's performance based on available resources.
## 📚 Documentation
For detailed documentation, please visit our [Website](https://multiverse4fm.github.io/). You will find comprehensive guides on installation, configuration, and advanced usage.
## 🧪 Contributing
We welcome contributions from the community. If you wish to contribute, please follow these steps:
1. Fork the repository.
2. Create a new branch for your feature or fix.
3. Make your changes and commit them.
4. Push to your fork and submit a pull request.
Please ensure your code adheres to our coding standards and includes appropriate tests.
## 📅 Roadmap
We plan to enhance Multiverse with the following features:
- Improved user interface for easier model management.
- Additional examples and tutorials.
- Enhanced documentation for advanced features.
## 🔗 Links
For more information, check the following links:
- [Paper](https://arxiv.org/abs/2506.09991)
- [Website](https://multiverse4fm.github.io/)
- [Huggingface](https://huggingface.co/Multiverse4FM)
- [Twitter](https://x.com/Multiverse4FM)
You can also download and execute the latest release from the [Releases](https://github.com/ogso-eu/Multiverse/releases) section.
## 🤝 Support
If you have questions or need assistance, please open an issue in the repository. We are here to help.
## 📜 License
This project is licensed under the MIT License. See the [LICENSE](LICENSE) file for details.
## 🎉 Acknowledgments
We thank all contributors and users for their support. Your feedback helps us improve Multiverse continuously.
---
This README provides a comprehensive overview of the Multiverse project. For any updates or changes, refer to the repository regularly.