# MilaNLProc/contextualized-topic-models

<https://repo.masters-masters.com/en/repos/MilaNLProc/contextualized-topic-models>

[Home](https://repo.masters-masters.com/en) › [MilaNLProc](https://repo.masters-masters.com/en/owners/MilaNLProc) › [contextualized-topic-models](https://repo.masters-masters.com/en/repos/MilaNLProc/contextualized-topic-models)

MilaNLProc/contextualized-topic-models has 1,275 stars on GitHub. Its RepoMasters card: Beta tier. A python package to run contextualized topic modeling. CTMs…

| Field | Value |
| --- | --- |
| Owner | [MilaNLProc](https://repo.masters-masters.com/en/owners/MilaNLProc) |
| Stars | 1,275 |
| Forks | 155 |
| Language | [Python](https://repo.masters-masters.com/en/languages/python) |
| License | MIT |
| Created | 2020 |
| Topics | topic-modeling, bert, transformer, embeddings, text-as-data, topic-coherence, multilingual-topic-models, multilingual-models, neural-topic-models, nlp |
| Tier | [Beta (700 to 1,999 ★)](https://repo.masters-masters.com/en/ranks/box_office) |
| View on GitHub | [MilaNLProc/contextualized-topic-models](https://github.com/MilaNLProc/contextualized-topic-models) |

## Repository

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.).

The tier for repos with 700 to 1,999 ★. Published odds per card pulled: 6%. Rarity: Rare.

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