Pretrained Models for Text Analysis
This is an R package to load and download a pretrained text analysis models. Some models are quite large and must be separately downloaded first. See also text2map.
Installation
library(remotes)
install_gitlab("culturalcartography/text2map.pretrained")
library(text2map.pretrained)Usage
A few smaller topic models are included when the package is installed:
| MODEL | N Docs |
|---|---|
| stm_envsoc | 817 |
| stm_fiction_cohort | 1,000 |
These can be loaded directly with data():
data("stm_envsoc")Word embedding models are much larger and must be first downloaded to your machine. Then they can be loaded with data():
# ~1 million fastText word vectors
mod <- "vecs_fasttext300_wiki_news"
# download the model once per machine
download_pretrained(mod)
# load the model each session
data(mod)
dim(wv)Below are the currently available word embedding models.
| MODEL | N TERMS | N DIMS | METHOD |
|---|---|---|---|
| vecs_fasttext300_wiki_news | 1,000,000 | 300 | fastText |
| vecs_fasttext300_wiki_news_subword | 1,000,000 | 300 | fastText |
| vecs_fasttext300_commoncrawl | 2,000,000 | 300 | fastText |
| vecs_glove300_wiki_gigaword | 400,000 | 300 | GloVe |
| vecs_sgns300_coha_histwords | 100,000 | 300 | SGNS |
| vecs_sgns300_googlenews | 1,000,000 | 300 | SGNS |
| vecs_sgns300_bnc_pos | 163,0000 | 300 | SGNS |
Contributions and Support
We welcome new models. If you have an embedding model or topic model you would like to be easily available to other researchers, send us an email (maintainers [at] textmapping.com) or submit pull requests.
Please report any issues or bugs here: https://gitlab.com/culturalcartography/text2map.pretrained/-/issues