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MLQ Distilbart Bbc

Developed by DeepNLP-22-23
This model is a text summarization model fine-tuned on the BBC News Summary dataset based on sshleifer/distilbart-cnn-12-6, developed by the Deep Natural Language Processing Course Lab at Politecnico di Torino.
Downloads 20
Release Time : 11/24/2022

Model Overview

This is a model specifically designed for summarizing BBC news texts, capable of generating concise summaries of news content.

Model Features

Efficient Summarization
Based on the DistilBART architecture, it reduces model size while maintaining performance.
BBC News Optimization
Fine-tuned specifically for BBC news content, making it suitable for news summarization tasks.
Lightweight
Fewer parameters compared to the original BART model, resulting in faster inference speed.

Model Capabilities

News Text Summarization
English Text Processing
Generating Concise Content

Use Cases

News Media
News Summary Generation
Automatically generates concise summaries for BBC news articles
ROUGE-2 score of 61.43
Content Aggregation
News Digest Creation
Automatically generates summary content for daily news digests
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