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).
Version: 1.0.3 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 Published: 2025-04-07 DOI: 10.32614/CRAN.package.pangoling Author: Bruno Nicenboim [aut, cre], Chris Emmerly [ctb], Giovanni Cassani [ctb], Lisa Levinson [rev], Utku Turk [rev] Maintainer: Bruno Nicenboim <b.nicenboim at tilburguniversity.edu> BugReports: https://github.com/ropensci/pangoling/issues License: MIT + file LICENSE URL: https://docs.ropensci.org/pangoling/, https://github.com/ropensci/pangoling NeedsCompilation: no Language: en-US Citation: pangoling citation info Materials: NEWS CRAN checks: pangoling results Documentation: Downloads: Linking:Please use the canonical form https://CRAN.R-project.org/package=pangoling to link to this page.
RetroSearch is an open source project built by @garambo | Open a GitHub Issue
Search and Browse the WWW like it's 1997 | Search results from DuckDuckGo
HTML:
3.2
| Encoding:
UTF-8
| Version:
0.7.4