contextualized-topic-models
A python package for contextualized topic modeling using BERT and other embeddings.
GraphCanon updated Sep 20, 2026 · GitHub synced Sep 20, 2026
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Decision brief
Contextualized-topic-models is a Python package that enhances traditional topic modeling by integrating contextualized embeddings like BERT.
Good fit when
- - When you need to analyze text data with enriched topic coherence provided by models utilizing BERT-like embeddings.
- - For research or development in NLP where multilingual or neural-specific topic analysis is required, as published in EACL and ACL 2021 by Bianchi et al.
Avoid when
- - If your project does not require advanced contextual embedding integration and more conventional topic modeling techniques suffice.
- - In scenarios where model complexity can be a bottleneck for real-time processing or when working with hardware limitations that cannot efficiently process BERT embeddings.
Observed Jul 12, 2026 · Source: enrich:decision_facts
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Maintenance and security
Full trust report- Maintenance
- Dormant (423d since push)
- As of Sep 20, 2026
- Provenance
- Not a fork · Organization account
- As of Sep 20, 2026
- Security (OSV)
- No lockfile
- As of Jul 11, 2026
Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.
Install
pip install contextualized-topic-modelsSimilar tools
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Evidence and technical details
Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.
Overview
This repository offers tools to combine contextualized embeddings like those from BERT with traditional topic models, enhancing the coherence of discovered topics. It is published in EACL and ACL 2021 by Bianchi et al., making it a valuable resource for researchers and developers working on advanced topic modeling within natural language processing.
Capability facts
- Languages
- python
Source: github.language · Sep 20, 2026
Categories
Compatibility
Sourced claims from the README excerpt - not unsourced marketing copy.
Source: README excerpt (regex_v1, Sep 20, 2026)
:target: https://pypi.python.org/pypi/contextualized_topic_modelsSource link
Tags
README
=========================== Contextualized Topic Models =========================== .. image:: https://img.shields.io/pypi/v/contextualized topic models.svg :target: https://pypi.python.org/pypi/contextualized topic models .. image:: https://github.com/MilaNLProc/contextualized t...
For agents
This page has a .md twin and JSON over the API.