bnosac/golgotha
Contextualised Embeddings and Language Modelling using BERT and Friends using R
This tool helps data analysts and researchers using R to understand and compare text by converting sentences into numerical representations. It takes raw text in various languages and produces 'embeddings' — numerical vectors that capture the meaning of words and sentences. This makes it easier to perform tasks like sentiment analysis, text classification, or finding similar documents, directly within your R environment.
No commits in the last 6 months.
Use this if you are an R user working with text data and need to convert it into a numerical format for downstream machine learning tasks, such as classifying customer feedback or identifying related news articles.
Not ideal if you are not familiar with the R programming language or prefer to work with text embeddings in a Python-native environment.
Stars
47
Forks
6
Language
R
License
MPL-2.0
Category
Last pushed
May 21, 2020
Commits (30d)
0
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