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sentencepiece  

Text Tokenization using Byte Pair Encoding and Unigram Modelling
View on CRAN: Click here


Download and install sentencepiece package within the R console
Install from CRAN:
install.packages("sentencepiece")

Install from Github:
library("remotes")
install_github("cran/sentencepiece")

Install by package version:
library("remotes")
install_version("sentencepiece", "0.2.4")



Attach the package and use:
library("sentencepiece")
Maintained by
Jan Wijffels
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2020-06-04
Latest Update: 2022-11-13
Description:
Unsupervised text tokenizer allowing to perform byte pair encoding and unigram modelling. Wraps the 'sentencepiece' library which provides a language independent tokenizer to split text in words and smaller subword units. The techniques are explained in the paper "SentencePiece: A simple and language independent subword tokenizer and detokenizer for Neural Text Processing" by Taku Kudo and John Richardson (2018) . Provides as well straightforward access to pretrained byte pair encoding models and subword embeddings trained on Wikipedia using 'word2vec', as described in "BPEmb: Tokenization-free Pre-trained Subword Embeddings in 275 Languages" by Benjamin Heinzerling and Michael Strube (2018) .
How to cite:
Jan Wijffels (2020). sentencepiece: Text Tokenization using Byte Pair Encoding and Unigram Modelling. R package version 0.2.4, https://cran.r-project.org/web/packages/sentencepiece. Accessed 05 Mar. 2026.
Previous versions and publish date:
0.1.1 (2020-06-04 12:10), 0.1.2 (2020-06-08 23:40), 0.2.1 (2021-12-21 17:00), 0.2.2 (2022-11-09 09:00), 0.2.3 (2022-11-13 10:30), 0.2.4 (2025-11-27 21:20), 0.2 (2021-12-15 00:00)
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Complete documentation for sentencepiece
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