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Dansumt5 Large
D
Dansumt5 Large
Developed by Danish-summarisation
Danish news summarization model based on the mT5-large architecture, trained on the DaNewsroom dataset, specifically designed for generating abstractive summaries of Danish news articles.
Downloads 20
Release Time : 4/10/2023
Model Overview
This model is a text summarization model based on Google's mT5 architecture, specifically optimized for Danish news articles, capable of generating high-quality abstractive summaries.
Model Features
Optimized for Danish news summarization
Specifically trained and optimized for Danish news articles, capable of generating summaries that match journalistic style.
Abstractive summarization generation
Capable of generating abstractive summaries rather than simple extractive summaries, providing more natural summary content.
Trained on large-scale dataset
Trained using the DaNewsroom dataset, which contains a large number of Danish news articles and their summaries.
Model Capabilities
Danish text comprehension
News article summarization
Abstractive text summarization
Use Cases
News media
Automatic news summarization
Automatically generate article summaries for Danish news websites
Improves reader efficiency by quickly conveying key news points
News aggregation platforms
Generate concise summaries of Danish news for news aggregation applications
Helps users quickly browse multiple news contents
Content analysis
News content analysis
Summarize large volumes of Danish news for subsequent analysis
Improves efficiency of news content analysis
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