HHousen/TransformerSum
Models to perform neural summarization (extractive and abstractive) using machine learning transformers and a tool to convert abstractive summarization datasets to the extractive task.
This tool helps researchers, analysts, and content creators quickly distill the essence of long documents like news articles, research papers, or how-to guides. It takes lengthy text as input and produces either a summary formed by extracting key sentences or a new, concise summary generated from scratch. This is ideal for anyone who needs to understand or convey the main points of extensive written material efficiently.
439 stars. No commits in the last 6 months.
Use this if you need to automatically generate clear, concise summaries from long documents, whether by extracting existing sentences or creating new summary text.
Not ideal if you need human-level nuance, creative writing, or summaries that require deep understanding beyond what statistical models can provide.
Stars
439
Forks
60
Language
Python
License
GPL-3.0
Category
Last pushed
May 26, 2025
Commits (30d)
0
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