SKTBrain/KoBERT

Korean BERT pre-trained cased (KoBERT)

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Established

KoBERT is a tool for anyone working with the Korean language who needs to understand meaning or categorize text. It takes raw Korean text as input and helps identify sentiment, recognize named entities like organizations or product names, or compare sentence meanings. This is ideal for natural language processing specialists, data scientists, or researchers focused on Korean text analysis.

1,407 stars. No commits in the last 6 months.

Use this if you need a highly accurate language model specifically pre-trained on a large volume of Korean text for tasks like sentiment analysis, named entity recognition, or semantic search.

Not ideal if your primary language of focus is not Korean, or if you require a very lightweight solution for simple keyword matching.

Korean-language-processing text-analytics sentiment-analysis named-entity-recognition semantic-search
Stale 6m No Package No Dependents
Maintenance 2 / 25
Adoption 10 / 25
Maturity 16 / 25
Community 25 / 25

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Stars

1,407

Forks

380

Language

Python

License

Apache-2.0

Last pushed

Jun 14, 2025

Commits (30d)

0

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