PeaTMOSS: Mining Pre-Trained Models in Open-Source Software
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Abstract (arXiv)
Developing and training deep learning models is expensive, so software engineers have begun to reuse pre-trained deep learning models (PTMs) and fine-tune them for downstream tasks. Despite the wide-spread use of PTMs, we know little about the corresponding software engineering behaviors and challenges. To enable the study of software engineering with PTMs, we present the PeaTMOSS dataset: Pre-Trained Models in Open-Source Software. PeaTMOSS has three parts: a snapshot of (1) 281,638 PTMs, (2) 27,270 open-source software repositories that use PTMs, and (3) a mapping between PTMs and the projects that use them. We challenge PeaTMOSS miners to discover software engineering practices around PTMs. A demo and link to the full dataset are available at: https://github.com/PurdueDualityLab/PeaTMOSS-Demos.
Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 19 of its 36 references that are in the map. First posted on arXiv 5 Oct 2023.
Builds on
19 of 36 references.
References · 19
- 2018On Testing Machine Learning Programscited by 48
- 2023An Empirical Study of Pre-Trained Model Reuse in the Hugging Face Deep Learning Model Registrycited by 47
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- 2021ModelDiff: Testing-Based DNN Similarity Comparison for Model Reuse Detectioncited by 33
- 2023Exploring the Carbon Footprint of Hugging Face's ML Models: A Repository Mining Studycited by 23
- 2022Threats to Pre-trained Language Models: Survey and Taxonomycited by 19
- 2021The Prevalence of Code Smells in Machine Learning projectscited by 16
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- 2023Challenges and Practices of Deep Learning Model Reengineering: A Case Study on Computer Visioncited by 11
- 2023Bug Characterization in Machine Learning-based Systemscited by 10
- 2023The Product Beyond the Model -- An Empirical Study of Repositories of Open-Source ML Productscited by 10
7 more
- 2022Scalpel: The Python Static Analysis Frameworkcited by 9
- 2019Understanding Flaky Tests: The Developer's Perspectivecited by 8
- 2022Code Smells for Machine Learning Applicationscited by 8
- 2023What Do Users Ask in Open-Source AI Repositories? An Empirical Study of GitHub Issuescited by 8
- 2020What Makes a Popular Academic AI Repository?cited by 6
- 2023Reusing Deep Neural Network Models through Model Re-engineeringcited by 6
- 2023Prevalence of Code Smells in Reinforcement Learning Projectscited by 3
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