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Distilbert Bert Summarization Cnn Dailymail
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Distilbert Bert Summarization Cnn Dailymail
Developed by Ayham
Text summarization model fine-tuned on the cnn_dailymail dataset, trained using the DistilBERT architecture
Downloads 19
Release Time : 3/2/2022
Model Overview
This model is a text summarization model based on the DistilBERT architecture, specifically optimized for news article summarization tasks.
Model Features
Efficient summarization
Capable of quickly generating concise summaries of news articles
Lightweight architecture
Based on DistilBERT, more lightweight and efficient than the full BERT model
News domain optimization
Specifically fine-tuned for the CNN/Daily Mail news dataset
Model Capabilities
Text summarization
News content understanding
Key information extraction
Use Cases
News media
News summarization generation
Automatically generate brief summaries of news articles
Helps readers quickly grasp the main content of articles
Content preview
Generate article previews for news platforms
Improves user click-through rates and reading experience
Information processing
Document summarization
Generate key point summaries for long documents
Enhances information processing efficiency
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