Supervised Machine Learning for Textual Data Using Transformers and 'Quanteda'

Duct tape the 'quanteda' ecosystem (Benoit et al., 2018) to modern Transformer-based text classification models (Wolf et al., 2020) , 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: .


Reference manual

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install.packages("grafzahl")

0.0.12 by Chung-hong Chan, a year ago


https://gesistsa.github.io/grafzahl/, https://github.com/gesistsa/grafzahl


Report a bug at https://github.com/gesistsa/grafzahl/issues


Browse source code at https://github.com/cran/grafzahl


Authors: Chung-hong Chan [aut, cre] (ORCID:


Documentation:   PDF Manual  


GPL (>= 3) license


Imports jsonlite, lime, quanteda, reticulate, utils, stats

Suggests knitr, quanteda.textmodels, rmarkdown, testthat, withr


See at CRAN