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News Sum Tr

Developed by nebiberke
A Turkish news text summarization model based on the mT5 architecture, trained on a dataset of Turkish economic and current affairs news, capable of generating core content summaries of news texts.
Downloads 30
Release Time : 11/10/2024

Model Overview

This model is primarily used to compress lengthy Turkish news articles into concise summaries, suitable for scenarios such as news aggregation platforms.

Model Features

Turkish Language Optimization
Specially optimized for Turkish news texts, better handling Turkish grammar and vocabulary characteristics.
Multi-dataset Training
Trained on two Turkish news datasets: batubayk/TR-News and denizzhansahin/100K-TR-News.
Efficient Summary Generation
Capable of compressing lengthy news articles into concise summaries of 30-150 tokens, retaining core content.

Model Capabilities

Turkish Text Understanding
News Content Summarization
Long Text Compression

Use Cases

News Aggregation
News Summary Platform
Automatically generates concise summaries for Turkish news, helping users quickly grasp key points.
Generates news summaries of 30-150 tokens, preserving core content.
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