https://gptzero.me/docs>). Allows users to classify text into human and computer written with probabilities. Formats the data into data frames where each sentence is an observation. Paragraph-level and document-level predictions are organized to align with the sentences.">

gptzeror: Identify Text Written by Large Language Models using 'GPTZero' (original) (raw)

An R interface to the 'GPTZero' API (<https://gptzero.me/docs>). Allows users to classify text into human and computer written with probabilities. Formats the data into data frames where each sentence is an observation. Paragraph-level and document-level predictions are organized to align with the sentences.

Version: 0.0.1
Imports: cli, curl, dplyr, httr2, lifecycle, tidyr
Suggests: httptest2, testthat (≥ 3.0.0)
Published: 2023-06-05
DOI: 10.32614/CRAN.package.gptzeror
Author: Christopher T. KennyORCID iD [aut, cre]
Maintainer: Christopher T. Kenny
BugReports: https://github.com/christopherkenny/gptzeror/issues
License: MIT + file
URL: https://github.com/christopherkenny/gptzeror,https://christophertkenny.com/gptzeror/
NeedsCompilation: no
Materials: README NEWS
CRAN checks: gptzeror results

Documentation:

Reference manual: gptzeror.pdf

Downloads:

Package source: gptzeror_0.0.1.tar.gz
Windows binaries: r-devel: gptzeror_0.0.1.zip, r-release: gptzeror_0.0.1.zip, r-oldrel: gptzeror_0.0.1.zip
macOS binaries: r-release (arm64): gptzeror_0.0.1.tgz, r-oldrel (arm64): gptzeror_0.0.1.tgz, r-release (x86_64): gptzeror_0.0.1.tgz, r-oldrel (x86_64): gptzeror_0.0.1.tgz

Linking:

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