Type: Package
Package: pangoling
Title: Access to Large Language Model Predictions
Version: 1.0.3
Authors@R: c(
person("Bruno", "Nicenboim", , "b.nicenboim@tilburguniversity.edu", role = c("aut", "cre"),
comment = c(ORCID = "0000-0002-5176-3943")),
person("Chris", "Emmerly", role = "ctb"),
person("Giovanni", "Cassani", role = "ctb"),
person("Lisa", "Levinson", role = "rev"),
person("Utku", "Turk", role = "rev")
)
Description: 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') 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)
,
for details on BERT and masked models, see Devlin et al. (2019)
. By enabling a straightforward
estimation of word predictability, the package facilitates
research in psycholinguistics, computational linguistics, and
natural language processing (NLP).
License: MIT + file LICENSE
URL: https://docs.ropensci.org/pangoling/,
https://github.com/ropensci/pangoling
BugReports: https://github.com/ropensci/pangoling/issues
Depends: R (>= 4.1.0)
Imports: cachem, data.table, memoise, reticulate, rstudioapi, stats,
tidyselect, tidytable (>= 0.7.2), utils
Suggests: brms, knitr, parallel, rmarkdown, spelling, testthat (>=
3.0.0), tictoc, covr
Config/testthat/edition: 3
Encoding: UTF-8
Language: en-US
LazyData: true
Roxygen: list(markdown = TRUE)
RoxygenNote: 7.3.1
StagedInstall: yes
VignetteBuilder: knitr
Config/pak/sysreqs: libpng-dev python3
Repository: https://ropensci.r-universe.dev
Date/Publication: 2026-01-13 15:59:45 UTC
RemoteUrl: https://github.com/ropensci/pangoling
RemoteRef: main
RemoteSha: 39916805ecb60c144f6a3bc531bfb7ff539f32d8
NeedsCompilation: no
Packaged: 2026-07-01 08:16:06 UTC; root
Author: Bruno Nicenboim [aut, cre] (ORCID:
),
Chris Emmerly [ctb],
Giovanni Cassani [ctb],
Lisa Levinson [rev],
Utku Turk [rev]
Maintainer: Bruno Nicenboim