dmmiller612/bert-extractive-summarizer

Health v2 · maintenance only

Adoption not part of the score

1453 stars · 306 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

A Python library for extractive text summarization using BERT embeddings via HuggingFace transformers. It embeds sentences, clusters them, and selects sentences closest to cluster centroids, with optional coreference resolution.

Use cases

• summarize long articles with python
• extract key sentences from a document
• summarize lecture transcripts
• get a short summary of text using BERT
• condense news articles into a few sentences
• summarize text with sentence transformers

When to choose

• you need extractive (not abstractive) summarization in Python
• you want a simple pip-installable summarizer with BERT or SBERT embeddings
• you need GPU-accelerated summarization with configurable sentence counts

When to avoid

• you need abstractive summaries that rewrite text
• you need a production service with active maintenance
• you cannot run transformer models due to compute constraints

Facets

library · maturity maintenance

nlp machine-learning machine-learning python bert extractive-summarization pytorch coreference sentence-embeddings natural-language-processing

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