Automated categorization of pre-trained models in software engineering: A case study with a Hugging Face dataset
Claudio Di Sipio, Riccardo Rubei, Juri Di Rocco, Davide Di Ruscio, Phuong T. Nguyen · 2024
Software engineering (SE) activities have been revolutionized by the advent of pre-trained models (PTMs), defined as large machine learning (ML) models that can be fine-tuned to perform specific SE tasks. However, users with limited expertise may need help to select the appropriate model for their current task. To tackle the issue, the Hugging Face (HF) platform simplifies the use of PTMs by collecting, storing, and curating several models. Nevertheless, the platform currently lacks a comprehensive categorization of PTMs designed specifically for SE, i.e., the existing tags are more suited to generic ML categories.