KeyBERT
Minimal keyword extraction library using BERT embeddings.
About
KeyBERT by Maarten Grootendorst is a minimal keyword and keyphrase extraction library that uses BERT embeddings to find the words and phrases most semantically similar to a document. It supports multiple embedding backends, diversification methods like maximal marginal relevance, and optional large language model integration, with a simple Python API. Released under the MIT license.
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Details
- Category
- Natural Language Processing
- Price
- Free
- Platform
- Local/Desktop
- Difficulty
- Beginner (1/5)
- License
- MIT
- Added
- Apr 3, 2026
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