mlsanityData to 7 Oct 2026

PyTorrent: A Python Library Corpus for Large-scale Language Models

arXiv 2110.01710 ↗First posted 4 Oct 2021cs.SEcited by 8

Not on the map. Why?

Abstract (arXiv)

A large scale collection of both semantic and natural language resources is essential to leverage active Software Engineering research areas such as code reuse and code comprehensibility. Existing machine learning models ingest data from Open Source repositories (like GitHub projects) and forum discussions (like Stackoverflow.com), whereas, in this showcase, we took a step backward to orchestrate a corpus titled PyTorrent that contains 218,814 Python package libraries from PyPI and Anaconda environment. This is because earlier studies have shown that much of the code is redundant and Python packages from these environments are better in quality and are well-documented. PyTorrent enables users (such as data scientists, students, etc.) to build off the shelf machine learning models directly without spending months of effort on large infrastructure. The dataset, schema and a pretrained language model is available at: https://github.com/fla-sil/PyTorrent

Key facts. Cited by 8 papers in the map (data through 7 Oct 2026). First posted on arXiv 4 Oct 2021.

Builds on

No reference list yet.

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 1; 2022: 3; 2023: 2; 2024: 1; 2025: 0; 2026: 1.

8 papers.