Contextualized Topic Models
Project description
Contextualized Topic Models
Contextualized Topic Models
Free software: MIT license
Documentation: https://contextualized-topic-models.readthedocs.io.
Super big shout-out to Stephen Carrow for creating the awesome https://github.com/estebandito22/PyTorchAVITM package from which we constructed the foundations of this package. We are happy to redistribute again this software under the MIT License.
Features
TODO
Quick Guide
Install the package using pip
pip install -U contextualized_topic_modelsThe contextual neural topic model can be easily instantiated using few parameters (although there is a wide range of parameters you can use to change the behaviour of the neural topic model.
cotm = COTM(input_size=1000, bert_input_size=512, inferencetype="contextual")
cotm.fit()See the example notebook in the contextualized_topic_models/examples folder
Team
Federico Bianchi <f.bianchi@unibocconi.it> Bocconi University
Silvia Terragni <s.terragni4@campus.unimib.it> University of Milan-Bicocca
Dirk Hovy <dirk.hovy@unibocconi.it> Bocconi University
Credits
This package was created with Cookiecutter and the audreyr/cookiecutter-pypackage project template. To ease the use of the library we have also incuded the rbo package, all the rights reserved to the author of that package.
History
0.1.0 (2020-04-04)
First release on PyPI.
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Source Distribution
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