Package: grafzahl 0.0.11

Chung-hong Chan

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

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>.

Authors:Chung-hong Chan [aut, cre]

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grafzahl.pdf |grafzahl.html
grafzahl/json (API)

# Install 'grafzahl' in R:
install.packages('grafzahl', repos = c('https://gesistsa.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/gesistsa/grafzahl/issues

Datasets:

On CRAN:

5.61 score 41 stars 2 scripts 203 downloads 8 exports 54 dependencies

Last updated 8 months agofrom:f340adce85. Checks:OK: 1 NOTE: 6. Indexed: yes.

TargetResultDate
Doc / VignettesOKOct 10 2024
R-4.5-winNOTEOct 10 2024
R-4.5-linuxNOTEOct 10 2024
R-4.4-winNOTEOct 10 2024
R-4.4-macNOTEOct 10 2024
R-4.3-winNOTEOct 10 2024
R-4.3-macNOTEOct 10 2024

Exports:detect_condadetect_cudaget_amharic_datagrafzahlhydratesetup_grafzahltextmodel_transformeruse_nonconda

Dependencies:assertthatclicodetoolscolorspacefansifarverfastmatchforeachggplot2glmnetgluegowergtablehereisobandISOcodesiteratorsjsonlitelabelinglatticelifecyclelimemagrittrMASSMatrixmgcvmunsellnlmepillarpkgconfigpngquantedaR6rappdirsRColorBrewerRcppRcppEigenRcppTOMLreticulaterlangrprojrootscalesshapeSnowballCstopwordsstringisurvivaltibbleutf8vctrsviridisLitewithrxml2yaml

Setup Guide

Rendered fromgrafzahl.Rmdusingknitr::rmarkdownon Oct 10 2024.

Last update: 2024-03-25
Started: 2024-03-25