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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>.
| Version: |
0.0.11 |
| Depends: |
R (≥ 3.5) |
| Imports: |
jsonlite, lime, quanteda, reticulate, utils, stats |
| Suggests: |
knitr, quanteda.textmodels, rmarkdown, testthat (≥ 3.0.0), withr |
| Published: |
2024-03-26 |
| Author: |
Chung-hong Chan 
[aut, cre] |
| Maintainer: |
Chung-hong Chan <chainsawtiney at gmail.com> |
| BugReports: |
https://github.com/gesistsa/grafzahl/issues |
| License: |
GPL (≥ 3) |
| URL: |
https://gesistsa.github.io/grafzahl/,
https://github.com/gesistsa/grafzahl |
| NeedsCompilation: |
no |
| Citation: |
grafzahl citation info |
| CRAN checks: |
grafzahl results |
Documentation:
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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