The experimentation lab to merge language models with ease.
Getting Started - Contributing - Issues - Website

👋 Welcome

Model merging is an innovative technique that allows you to combine pre-trained and fine-tuned language models (LMs) into new models with unique capabilities.

This package is a fully open-source client that streamlines your merging operations with the convenience of a GUI interface. Underneath, flow-merge-ui is based on the flow-merge library.

flow-merge is a fully open-source library written in Python that implements some of the most popular merge methods such as model soups, SLERP, ties-MERGING or DARE. The library is built on top of the Hugging Face transformers library and the deep learning framework Pytorch, and provides a simple and easy-to-use interface to merge models and upload them to the Hugging Face Hub. Visit flow-merge.com to learn more about the library.

⭐️ Features

flow-merge-ui has been designed to expedite and streamline merging operations performed with the underlying flow-merge library. Hence, acting as an experimentation lab for the library.

Note: flow-merge is packaged with flow-merge-ui and hence is locked to a specific version.

The lab allows you to configure relevant parameters for the merge, such as:

• Merging method: The method with which to merge models.
• Merging method parameters: Fine tuning the method outcomes with respective paramenters. For example top_k, scaling_coefficient, and drop_rate (p)
• Models: Models to merge.
• Tokenizer configuration: Tokenizer mode and interpolation method.

The key features of the lab consists of:

• Pulling from Hugging Face Hub: Integrates with HF hub and pulls a complete list of models available for merging. Downloads the model as pre-requisite step of the merging operation.
• Pushing to Hugging face Hub: Once a merge completes, you can easily push the merged model to your Hugging face registry.
• Merge history: Keep track of your recent merges, respective configurations and push merged models to HF hub with ease using a merge history candidate.
• Logs and debugging: Logs are propagated to the UI once a merge operation is in process.

🎉 Getting started

🛠️ Project structure

There are two primary services that make up this application. A python Fast API backend and a Vue UI served via nginx. The database is SQLite.

.
├── api                     # API directory
    ├── src                 # API files
    ├── .env.example        # Example env variables
    ├── Dockerfile          # Dockerfile for the API layer
├── app                     # UI directory
    ├── src                 # source files
    ├── .env.example        # Example env variables
    ├── Dockerfile          # Dockerfile that defines UI serving via nginx
├── docker-compose.yml      # Docker compose uses built images from <dir>/Dockerfile
├── LICENSE
└── README.md

🏎️💨 Quick start

1. Clone the repository and navigate to the root directory:

# via ssh
git clone git@github.com:flowritecom/flow-merge-ui.git

cd flow-merge-ui

2. Create a .env file for app/.env and api/.env. You can use the example environment files defined in the respective directories to populate the respective variables.

3. Run the complete client application using docker & docker compose. We've abstracted away the docker commands with Makefile rules:

# build the client and backend images
make
# run docker compose
make up

If make is not an option, simply build and run with docker & docker compose:

# from the root directory
docker build -t flow_merge_ui/frontend -f ./app/Dockerfile ./app
docker build -t flow_merge_ui/backend -f ./api/Dockerfile ./api
# run docker compose
docker compose -p flow_merge_ui -f docker-compose.yml up -d

Apply database migrations:

make docker-sqlite-migrate

To bring the migrations down:

make docker-sqlite-migrate-down

📚 Additional resources

Visit the flow-merge Github page for details on the supported methods, LLM architectues, and properties of the methods.

🗺️ flow-merge-ui Roadmap

Coming soon..

✨ Project showcase

Coming soon..

🤝 Contributing

Wanna pitch in? We're totally open to contributions for the core flow-merge library as well as any cool integrations built on top of it! Check out our Contribution Guide for all the details on how to get started.