MilaNLProc/contextualized-topic-models

A python package to run contextualized topic modeling. CTMs combine contextualized embeddings (e.g., BERT) with topic models to get coherent topics. Published at EACL and ACL 2021 (Bianchi et al.).

1.3k 151 +0/wk

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bert embeddings multilingual-models multilingual-topic-models neural-topic-models nlp nlp-library nlp-machine-learning text-as-data topic-coherence topic-modeling transformer

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Star & Fork Trend (32 data points)

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GitHub

stars 1.3k

forks 151

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MilaNLProc/contextualized-topic-models has +0 stars this period . Velocity data will be available after more historical data is collected.

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Metric	contextualized-topic-models	KGQA-Based-On-medicine	Transformers4Rec	detext
Stars	1.3k	1.3k	1.3k	1.3k
Forks	151	288	159	134
Weekly Growth	+0	+0	+2	-1
Language	Python	JavaScript	Python	Python
Sources	1	1	1	1
License	MIT	N/A	Apache-2.0	BSD-2-Clause

Capability Radar vs KGQA-Based-On-medicine

contextualized-topic-models

KGQA-Based-On-medicine

Maintenance Activity 0

Last code push 259 days ago.

Community Engagement 60

Fork-to-star ratio: 11.9%. Active community forking and contributing.

Issue Burden 70

Issue data not yet available.

Growth Momentum 30

No measurable growth in the current period (first-day cold start expected).

License Clarity 95

Licensed under MIT. Permissive — safe for commercial use.

Risk scores are computed from real-time repository data. Higher scores indicate healthier metrics.