Text-Summarizer and Text-Summarization

These are competitors offering overlapping functionality—both implement transformer-based text summarization with similar abstractive and extractive approaches, so users would typically select one based on model performance comparisons rather than use them together.

Text-Summarizer
31
Emerging
Text-Summarization
35
Emerging
Maintenance 0/25
Adoption 6/25
Maturity 9/25
Community 16/25
Maintenance 0/25
Adoption 9/25
Maturity 16/25
Community 10/25
Stars: 19
Forks: 6
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 Text-Summarizer

singhsidhukuldeep/Text-Summarizer

Comparing state of the art models for text summary generation

About Text-Summarization

aj-naik/Text-Summarization

Abstractive and Extractive Text summarization using Transformers.

Scores updated daily from GitHub, PyPI, and npm data. How scores work