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A collection of large language model (LLM) text analysis methods designed with psychological data in mind. Currently, LLMing (aka "lemming") includes a text anomaly detection method based on the angle-based subspace approach described by Zhang, Lin, and Karim (2015) and a text generation method. <doi:10.1016/j.ress.2015.05.025>.
| Version: | 1.1.0 |
| Depends: | R (≥ 4.1.0) |
| Imports: | Rdpack, quanteda, stopwords, stringi, reticulate, text, dbscan, pracma, stats, jsonlite |
| Published: | 2026-01-08 |
| DOI: | 10.32614/CRAN.package.LLMing |
| Author: | Lindley Slipetz [aut, cre], Teague Henry [aut], Siqi Sun [ctb] |
| Maintainer: | Lindley Slipetz <ddj6tu at virginia.edu> |
| BugReports: | https://github.com/sliplr19/LLMing/issues |
| License: | MIT + file LICENSE |
| URL: | https://github.com/sliplr19/LLMing |
| NeedsCompilation: | no |
| SystemRequirements: | Python (>= 3.10) with packages: torch, transformers, pandas, numpy |
| Materials: | README, NEWS |
| CRAN checks: | LLMing results |
| Reference manual: | LLMing.html , LLMing.pdf |
| Package source: | LLMing_1.1.0.tar.gz |
| Windows binaries: | r-devel: LLMing_1.1.0.zip, r-release: LLMing_1.1.0.zip, r-oldrel: LLMing_1.1.0.zip |
| macOS binaries: | r-release (arm64): LLMing_1.1.0.tgz, r-oldrel (arm64): LLMing_1.1.0.tgz, r-release (x86_64): LLMing_1.1.0.tgz, r-oldrel (x86_64): LLMing_1.1.0.tgz |
| Old sources: | LLMing archive |
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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.