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fastText

R package for 'Efficient Learning of Word Representations and Sentence Classification'

https://github.com/mlampros/fasttext

Science Score: 26.0%

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    CITATION.cff file
  • ✓
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    Found codemeta.json file
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    Found .zenodo.json file
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  • ○
    Scientific vocabulary similarity
    Low similarity (16.1%) to scientific vocabulary

Keywords

cpp11 fasttext r
Last synced: 6 months ago · JSON representation

Repository

R package for 'Efficient Learning of Word Representations and Sentence Classification'

Basic Info
Statistics
  • Stars: 45
  • Watchers: 3
  • Forks: 5
  • Open Issues: 0
  • Releases: 0
Topics
cpp11 fasttext r
Created almost 7 years ago · Last pushed about 2 years ago
Metadata Files
Readme Changelog License

README.Rmd 

---
output: github_document
---

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## 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*)




![](./man/figures/skipgram_vs_cbow.png)




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

 


![](./man/figures/static_contextualised_word_embeddings.png)




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},
}
```

Owner

  • Name: Lampros Mouselimis
  • Login: mlampros
  • Kind: user

Search (a little bit) and you'll find...

GitHub Events

Total
  • Watch event: 4
Last Year
  • Watch event: 4

Committers

Last synced: over 1 year ago

All Time
  • Total Commits: 13
  • Total Committers: 2
  • Avg Commits per committer: 6.5
  • Development Distribution Score (DDS): 0.077
Past Year
  • Commits: 1
  • Committers: 1
  • Avg Commits per committer: 1.0
  • Development Distribution Score (DDS): 0.0
Top Committers
Name Email Commits
Lampros Mouselimis m****s@g****m 12
Tomas Kalibera t****a@g****m 1

Issues and Pull Requests

Last synced: 6 months ago

All Time
  • Total issues: 4
  • Total pull requests: 1
  • Average time to close issues: 9 days
  • Average time to close pull requests: about 3 hours
  • Total issue authors: 4
  • Total pull request authors: 1
  • Average comments per issue: 5.25
  • Average comments per pull request: 1.0
  • Merged pull requests: 1
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 0
  • Pull requests: 0
  • Average time to close issues: N/A
  • Average time to close pull requests: N/A
  • Issue authors: 0
  • Pull request authors: 0
  • Average comments per issue: 0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
View more stats
Top Authors
Issue Authors
  • jesuiskelly (1)
  • karrtikiyer (1)
  • datawranglerai (1)
Pull Request Authors
  • kalibera (2)
Top Labels
Issue Labels
bug (1) triage (1)
Pull Request Labels

Packages

  • Total packages: 1
  • Total downloads:
    • cran 351 last-month
  • Total docker downloads: 16
  • Total dependent packages: 0
  • Total dependent repositories: 0
  • Total versions: 5
  • Total maintainers: 1
cran.r-project.org: fastText

Efficient Learning of Word Representations and Sentence Classification

  • Versions: 5
  • Dependent Packages: 0
  • Dependent Repositories: 0
  • Downloads: 351 Last month
  • Docker Downloads: 16
Rankings
Stargazers count: 8.4%
Forks count: 12.8%
Average: 23.7%
Dependent packages count: 29.8%
Downloads: 32.0%
Dependent repos count: 35.5%
Maintainers (1)
mouselimislampros@gmail.com
Last synced: 6 months ago

Dependencies

.github/workflows/issue.yml actions
  • Renato66/auto-label v2 composite
.github/workflows/stale-actions.yml actions
  • actions/stale v3 composite
.github/workflows/tic.yml actions
  • actions/checkout v3 composite
  • actions/upload-artifact v2.2.1 composite
  • pat-s/always-upload-cache v2.1.3 composite
  • r-lib/actions/setup-pandoc v2 composite
  • r-lib/actions/setup-r v2 composite
  • r-lib/actions/setup-tinytex v2 composite
DESCRIPTION cran
  • R >= 3.2.3 depends
  • Rcpp >= 1.0.0 imports
  • data.table * imports
  • ggplot2 * imports
  • glue * imports
  • grid * imports
  • stats * imports
  • utils * imports
  • covr * suggests
  • knitr * suggests
  • rmarkdown * suggests
  • testthat * suggests