arXiv Computer Science
arXiv Computer Science
Preprint
3 years ago

Small-text: Active Learning for Text Classification in Python. (arXiv:2107.10314v1 [cs.LG])

Christopher Schröder, Lydia Müller, Andreas Niekler, Martin Potthast
We present small-text, a simple modular active learning library, which offers pool-based active learning for text classification in Python. It comes with various pre-implemented state-of-the-art query strategies, including some which can leverage the GPU. Clearly defined interfaces allow to combine a multitude of such query strategies with different classifiers, thereby facilitating a quick mix and match, and enabling a rapid development of both active learning experiments and applications. To make various classifiers accessible in a consistent way, it integrates several well-known machine learning libraries, namely, scikit-learn, PyTorch, and huggingface transformers -- for which the latter integrations are available as optionally installable extensions. The library is available under the MIT License at https://github.com/webis-de/small-text.

Publisher URL: http://arxiv.org/abs/2107.10314

DOI: arXiv:2107.10314v1

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