Git-Theta: A Git Extension for Collaborative Development of Machine Learning Models

TL;DR

Git-Theta is a novel extension to Git that enables collaborative, fine-grained version control of machine learning models, supporting efficient updates, automatic merges, and meaningful change reports to facilitate shared model development.

Contribution

It introduces Git-Theta, the first version control system tailored for machine learning models, allowing structured tracking and collaborative development of models.

Findings

Supports communication-efficient model updates

Enables automatic merging of model versions

Provides meaningful diff reports for models

Abstract

Currently, most machine learning models are trained by centralized teams and are rarely updated. In contrast, open-source software development involves the iterative development of a shared artifact through distributed collaboration using a version control system. In the interest of enabling collaborative and continual improvement of machine learning models, we introduce Git-Theta, a version control system for machine learning models. Git-Theta is an extension to Git, the most widely used version control software, that allows fine-grained tracking of changes to model parameters alongside code and other artifacts. Unlike existing version control systems that treat a model checkpoint as a blob of data, Git-Theta leverages the structure of checkpoints to support communication-efficient updates, automatic model merges, and meaningful reporting about the difference between two versions of a model. In addition, Git-Theta includes a plug-in system that enables users to easily add support for new functionality. In this paper, we introduce Git-Theta's design and features and include an example use-case of Git-Theta where a pre-trained model is continually adapted and modified. We publicly release Git-Theta in hopes of kickstarting a new era of collaborative model development.