https://github.com/mlampros/fasttext
R package for 'Efficient Learning of Word Representations and Sentence Classification'
https://github.com/mlampros/fasttext
cpp11 fasttext r
Last synced: 8 months ago
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R package for 'Efficient Learning of Word Representations and Sentence Classification'
- Host: GitHub
- URL: https://github.com/mlampros/fasttext
- Owner: mlampros
- License: other
- Created: 2019-04-11T19:13:54.000Z (about 7 years ago)
- Default Branch: master
- Last Pushed: 2024-02-15T10:18:34.000Z (over 2 years ago)
- Last Synced: 2025-04-11T01:49:11.462Z (about 1 year ago)
- Topics: cpp11, fasttext, r
- Language: C++
- Homepage: https://mlampros.github.io/fastText/
- Size: 3.34 MB
- Stars: 42
- Watchers: 3
- Forks: 5
- Open Issues: 0
-
Metadata Files:
- Readme: README.Rmd
- License: LICENSE
Awesome Lists containing this project
README
---
output: github_document
---
[](https://github.com/mlampros/fastText/actions)
[](https://codecov.io/github/mlampros/fastText?branch=master)
[](http://cran.r-project.org/package=fastText)
[](http://www.r-pkg.org/pkg/fastText)
[](https://cran.r-project.org/package=fastText)
## fastText
The **fastText** R package is an interface to the [fastText](https://github.com/facebookresearch/fastText) library for efficient learning of word representations and sentence classification. More details on the functionality of fastText can be found in the
* [fastText_updated_version](http://mlampros.github.io/2019/04/11/fastText_updated_version/) (blog post)
* [fasttext_language_identification](http://mlampros.github.io/2021/05/14/fasttext_language_identification/) (blog post)
* [package documentation](https://mlampros.github.io/fastText/reference/index.html).
The [official website of the fasttext algorithm](https://fasttext.cc/) includes more details regarding the supervised & unsupervised functions. The following image shows the difference between [**cbow** and **skipgram**](https://fasttext.cc/docs/en/unsupervised-tutorial.html#advanced-readers-skipgram-versus-cbow) (*models to compute word representations*)

Moreover, the following figure - extracted from [a survey (scientific paper) related to word embeddings](https://hal.science/hal-03148517/document) and recent advancements in Large Language Models - shows the differences between *static* and *contextualized* word embeddings

You can either install the package from CRAN using,
```R
install.packages("fastText")
```
or from Github using the *install_github* function of the *remotes* package,
```R
remotes::install_github('mlampros/fastText')
```
**or** directly download the fastText-zip file using the **Clone or download** button in the [repository page](https://github.com/mlampros/fastText), extract it locally (rename it to *fastText* if necessary and check that files such as DESCRIPTION, NAMESPACE etc. are present when you open the fastText folder) and then run,
```R
#-------------
# on a Unix OS
#-------------
setwd('/your_folder/fastText/')
Rcpp::compileAttributes(verbose = TRUE)
setwd('/your_folder/')
system("R CMD build fastText")
system("R CMD INSTALL fastText_1.0.1.tar.gz")
#------------------
# on the Windows OS
#------------------
setwd('C:/your_folder/fastText/')
Rcpp::compileAttributes(verbose = TRUE)
setwd('C:/your_folder/')
system("R CMD build fastText")
system("R CMD INSTALL fastText_1.0.1.tar.gz")
```
Use the following link to report bugs/issues (for the R package port),
[https://github.com/mlampros/fastText/issues](https://github.com/mlampros/fastText/issues)
### **Citation:**
If you use the **fastText** R package in your paper or research please cite both **fastText** and the **original articles / software** `https://CRAN.R-project.org/package=fastText`:
```R
@Manual{,
title = {{fastText}: Efficient Learning of Word Representations and
Sentence Classification using R},
author = {Lampros Mouselimis},
year = {2021},
note = {R package version 1.0.3},
url = {https://CRAN.R-project.org/package=fastText},
}
```