good-soup 0.0.1
A tool for making model souping ultra-simple, easy and fast!
License: Apache 2.0
Requires Python: >=3.10
Keywords: model souping, merging, llm

<div align="center">

![🥫🥣👌](./assets/good_soup.png)

# 🥣 Good Soup 👌

_Stirring up SOTA models with ease! A tool for making model souping ultra-simple, fast and easy!_

[![PyPI](https://badge.fury.io/py/good-soup.svg)](https://badge.fury.io/py/good-soup)
[![Documentation](https://img.shields.io/badge/docs-DOCS-blue.svg)](DOCS.md)
[![License](https://img.shields.io/badge/License-Apache%202.0-blue.svg)](LICENSE)
[![Stars](https://img.shields.io/github/stars/chonkie-inc/good-soup?style=social)](https://github.com/chonkie-inc/good-soup)

</div>

Model souping is like being a chef in the world of AI 🧑‍🍳. You take a few well-trained models (your ingredients 🥦🥩🥕), mix their weights together (stir the pot!🥣), and voilà! You often end up with a *new* model that performs better than any of the individual ingredients. It's a fantastic technique for pushing the boundaries and achieving State-of-the-Art (SOTA) results.

But let's be honest, sometimes the recipe can be complicated. Setting up the kitchen, getting the measurements right... it can be a hassle. That's where `Good Soup` comes in! We handle the messy parts so you can focus on the delicious results. 👌

## 🚀 Getting Started

We want `Good Soup` to be as easy as opening a can. The ultimate goal is a simple `pip install`:

```bash
# Soon! 🙏
pip install good-soup 
```

For now, you'll need to grab it fresh from the source:

```bash
git clone https://github.com/chonkie-inc/good-soup.git
cd good-soup
pip install -e . 
```

## 🧑‍🍳 Usage Example

Whipping up a soup is super simple:

```python
from good_soup import Soup

# Create your soup object
soup = Soup(
    # List of paths to the models you want to blend 🥣
    models=[
        "path/to/model_1.bin", 
        "path/to/model_2.bin",
        # Add as many models as you like!
    ], 
    # The merging strategy (more recipes coming soon!) 📜
    # 'uniform' averages the weights of all models.
    method="uniform", 
    # Where to save your delicious new model 🍲
    output_dir="path/to/output_dir", 
    # Optional: Specify data type (e.g., 'float16', 'bfloat16')
    # dtype="float16", 
    # Optional: Specify device ('cpu', 'cuda')
    # device="cuda", 
)

# That's it! Your souped model is ready in output_dir.
print("Soup's ready! 👌") 
```

## 📜 Available Recipes (Methods)

Currently, `Good Soup` offers one classic recipe:

*   **`uniform`**: This method simply averages the weights of all provided models. It's a great starting point and often yields surprisingly good results!

Keep an eye out! We're constantly experimenting in the kitchen and plan to add more sophisticated recipes like `greedy` merging, `ties`, and `dare` soon! 🧑‍🔬

## 🗺️ Roadmap

*   [ ] Add `greedy` souping method.
*   [ ] Add `ties` merging method.
*   [ ] Add `dare` merging method.
*   [ ] Publish to PyPI for easy `pip install`.
*   [ ] More comprehensive documentation and examples.
*   [ ] Support for different model formats (e.g., SafeTensors).

## 🙌 Contributing

Want to add your own spice to the soup? Contributions are welcome! Feel free to open an issue or submit a pull request. Let's cook up something great together! 🤝

## 🙏 Acknowledgements

> CHONKIE loves soup! 🥣👌

A huge thank you to [Adam Driver](https://en.wikipedia.org/wiki/Adam_Driver) – a true inspiration and a connoisseur of fine soup (probably).

And thanks to the amazing open-source community for providing the quality ingredients that make this project possible!

## ✍️ Citation

If `Good Soup` helps you in your research or project, please cite it:

```bibtex
@misc{goodsoup2025,
  author = {Chonkie Inc.},
  title = {Good Soup: A tool for making model souping ultra-simple, easy and fast!},
  year = {2025},
  publisher = {GitHub},
  journal = {GitHub repository},
  url = {https://github.com/chonkie-inc/good-soup}
}
```