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pangoling  

Access to Large Language Model Predictions
View on CRAN: Click here


Download and install pangoling package within the R console
Install from CRAN:
install.packages("pangoling")

Install from Github:
library("remotes")
install_github("cran/pangoling")

Install by package version:
library("remotes")
install_version("pangoling", "1.0.3")



Attach the package and use:
library("pangoling")
Maintained by
Bruno Nicenboim
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2025-04-07
Latest Update: 2025-04-07
Description:
Provides access to word predictability estimates using large language models (LLMs) based on 'transformer' architectures via integration with the 'Hugging Face' ecosystem <https://huggingface.co/>. The package interfaces with pre-trained neural networks and supports both causal/auto-regressive LLMs (e.g., 'GPT-2') and masked/bidirectional LLMs (e.g., 'BERT') to compute the probability of words, phrases, or tokens given their linguistic context. For details on GPT-2 and causal models, see Radford et al. (2019) <https://storage.prod.researchhub.com/uploads/papers/2020/06/01/language-models.pdf>, for details on BERT and masked models, see Devlin et al. (2019) <doi:10.48550/arXiv.1810.04805>. By enabling a straightforward estimation of word predictability, the package facilitates research in psycholinguistics, computational linguistics, and natural language processing (NLP).
How to cite:
Bruno Nicenboim (2025). pangoling: Access to Large Language Model Predictions. R package version 1.0.3, https://cran.r-project.org/web/packages/pangoling. Accessed 18 Sep. 2026.
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