Package: sbert Type: Package Title: Topic Modeling with 'Sentence-BERT' Embeddings Version: 0.5.8 Authors@R: c( person( given = "Mohammed", family = "Saqr", role = c("aut", "cph"), email = "mohammed.saqr@uef.fi", comment = c(ORCID = "0000-0001-5881-3109") ), person( given = "Sonsoles", family = "L\u00f3pez-Pernas", role = c("aut", "cre", "cph"), email = "sonsoles.lopez@uef.fi", comment = c(ORCID = "0000-0002-9621-1392") ) ) Description: Builds semantic topic models from 'Sentence-BERT' embeddings (Reimers and Gurevych, 2019) . Sentence embeddings are computed in several modes with models run on the Open Neural Network Exchange ('ONNX') Runtime, including multilingual and long-context encoders and a fast static model. Topics are labeled with class-based term weighting that can be retuned without refitting. Candidate topic counts and document granularities (whole documents, sentences, clauses, or phrases) can be compared side by side, and fitted models assign topics to new documents, give soft memberships and per-document topic mixtures. The package offers coherence and diversity metrics and visualizations. License: MIT + file LICENSE URL: https://sonsoles.me/sbert/, https://github.com/sonsoleslp/sbert BugReports: https://github.com/sonsoleslp/sbert/issues Encoding: UTF-8 Language: en-US LazyData: true Depends: R (>= 4.1.0) Imports: digest, grDevices, graphics, onnxr (>= 0.1.2), parallel, tok (>= 0.2.3), stats, tools, utils Suggests: SnowballC, jsonlite, knitr, rmarkdown, testthat (>= 3.0.0), withr SystemRequirements: ONNX Runtime (>= 1.25.1) VignetteBuilder: knitr Config/testthat/edition: 3 RoxygenNote: 8.0.0 Config/pak/sysreqs: libclang-dev Repository: https://mohsaqr.r-universe.dev Date/Publication: 2026-10-09 17:03:24 UTC RemoteUrl: https://github.com/sonsoleslp/sbert RemoteRef: HEAD RemoteSha: 387023d12ebc6cc73b8a32332fcc60c56ad79af7 NeedsCompilation: no Packaged: 2026-10-09 21:08:53 UTC; root Author: Mohammed Saqr [aut, cph] (ORCID: ), Sonsoles López-Pernas [aut, cre, cph] (ORCID: ) Maintainer: Sonsoles López-Pernas