Int2Int: a framework for mathematics with transformers
This framework addresses the need for accessible tools to apply transformers to mathematical problems, though it is incremental as it builds on existing transformer architectures.
The authors introduced Int2Int, an open-source framework for applying transformer models to mathematical research problems, particularly in number theory and integer-related domains, providing a complete PyTorch implementation with training, evaluation, and visualization tools.
This paper documents Int2Int, an open source code base for using transformers on problems of mathematical research, with a focus on number theory and other problems involving integers. Int2Int is a complete PyTorch implementation of a transformer architecture, together with training and evaluation loops, and classes and functions to represent, generate and decode common mathematical objects. Ancillary code for data preparation, and Jupyter Notebooks for visualizing experimental results are also provided. This document presents the main features of Int2Int, serves as its user manual, and provides guidelines on how to extend it. Int2Int is released under the MIT licence, at https://github.com/f-charton/Int2Int.