transformer-abstractive-summarization and Text-Summarization

These are competitors offering overlapping functionality—both implement transformer-based abstractive summarization—though A focuses exclusively on the abstractive approach while B adds extractive methods as an alternative summarization strategy.

Maintenance 0/25
Adoption 10/25
Maturity 16/25
Community 22/25
Maintenance 0/25
Adoption 9/25
Maturity 16/25
Community 10/25
Stars: 168
Forks: 47
Downloads:
Commits (30d): 0
Language: Jupyter Notebook
License: Apache-2.0
Stars: 86
Forks: 7
Downloads:
Commits (30d): 0
Language: Jupyter Notebook
License: MIT
Stale 6m No Package No Dependents
Stale 6m No Package No Dependents

About transformer-abstractive-summarization

rojagtap/transformer-abstractive-summarization

Abstractive Text Summarization using Transformer

This helps content creators, journalists, or marketers quickly condense lengthy articles into short, human-like summaries. You provide a long news article or text, and it generates a concise, readable abstract that captures the main points. This is useful for anyone needing to grasp key information quickly or to produce brief content without manual rephrasing.

content-creation news-briefing digital-marketing information-digestion journalism

About Text-Summarization

aj-naik/Text-Summarization

Abstractive and Extractive Text summarization using Transformers.

This project helps students, researchers, or anyone dealing with large volumes of text quickly grasp the main points. You provide it with a long document, article, or research paper, and it generates either a condensed version highlighting key sentences or a completely new, shorter summary in your own words. It's designed for anyone needing to efficiently process information and get to the core message without reading everything.

academic-research content-analysis information-retrieval study-notes report-writing

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