Going Beyond T-SNE: Exposing \texttt{whatlies} in Text Embeddings

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Authors Rachael Tatman, Vincent D. Warmerdam, Thomas Kober
Journal/Conference Name arXiv preprint
Paper Category
Paper Abstract We introduce whatlies, an open source toolkit for visually inspecting word and sentence embeddings. The project offers a unified and extensible API with current support for a range of popular embedding backends including spaCy, tfhub, huggingface transformers, gensim, fastText and BytePair embeddings. The package combines a domain specific language for vector arithmetic with visualisation tools that make exploring word embeddings more intuitive and concise. It offers support for many popular dimensionality reduction techniques as well as many interactive visualisations that can either be statically exported or shared via Jupyter notebooks. The project documentation is available from https//rasahq.github.io/whatlies/.
Date of publication 2020
Code Programming Language Python
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