Small-text

Small-text: Active Learning for Text Classification in Python. 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.

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References in zbMATH (referenced in 1 article , 1 standard article )

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  1. Christopher Schröder, Lydia Müller, Andreas Niekler, Martin Potthast: Small-text: Active Learning for Text Classification in Python (2021) arXiv