Mergenetic: a Simple Evolutionary Model Merging Library
Authors: name: Adrian Robert Minut, name: Tommaso Mencattini, name: Andrea Santilli, name: Donato Crisostomi, name: Emanuele Rodolà

Model merging allows combining the capabilities of existing models into a new
one - post hoc, without additional training. This has made it increasingly
popular thanks to its low cost and the availability of libraries that support
merging on consumer GPUs. Recent work shows that pairing merging with
evolutionary algorithms can boost performance, but no framework currently
supports flexible experimentation with such strategies in language models. We
introduce Mergenetic, an open-source library for evolutionary model merging.
Mergenetic enables easy composition of merging methods and evolutionary
algorithms while incorporating lightweight fitness estimators to reduce
evaluation costs. We describe its design and demonstrate that Mergenetic
produces competitive results across tasks and languages using modest hardware.