Package: pangoling 1.0.1

pangoling: Access to Large Language Model Predictions

Provides access to word predictability estimates using large language models (LLMs) based on 'transformer' architectures via integration with the 'Hugging Face' ecosystem. The package interfaces with pre-trained neural networks and supports both causal/auto-regressive LLMs (e.g., 'GPT-2'; Radford et al., 2019) and masked/bidirectional LLMs (e.g., 'BERT'; Devlin et al., 2019, <doi:10.48550/arXiv.1810.04805>) to compute the probability of words, phrases, or tokens given their linguistic context. By enabling a straightforward estimation of word predictability, the package facilitates research in psycholinguistics, computational linguistics, and natural language processing (NLP).

Authors:Bruno Nicenboim [aut, cre], Chris Emmerly [ctb], Giovanni Cassani [ctb], Lisa Levinson [rev], Utku Turk [rev]