Supervised Machine Learning for Textual Data Using Transformers and 'Quanteda' R package grafzahl version 0.0.12 Duct tape the 'quanteda' ecosystem (Benoit et al., 2018) <doi:10.21105/joss.00774> to modern Transformer-based text classification models (Wolf et al., 2020) <doi:10.18653/v1/2020.emnlp-demos.6>, in order to facilitate supervised machine learning for textual data. This package mimics the behaviors of 'quanteda.textmodels' and provides a function to setup the 'Python' environment to use the pretrained models from 'Hugging Face' <https://huggingface.co/>. More information: <doi:10.5117/CCR2023.1.003.CHAN>. Software Depends: R (>= 3.5) Imports: jsonlite, lime, quanteda, reticulate, utils, stats Suggests: knitr, quanteda.textmodels, rmarkdown, testthat (>= 3.0.0), withr Chung-hong Chan <chainsawtiney@gmail.com> Comprehensive R Archive Network (CRAN) Chung-hong Chan [aut, cre] (ORCID: <https://orcid.org/0000-0002-6232-7530>) GPL (>= 3) 2025-06-18 application/tgz https://CRAN.R-project.org/package=grafzahl doi:10.32614/CRAN.package.grafzahl