Open-source text summarization model for bert_roberta_summarization_cnn_dailymail - Free and accurate text summarization implementation

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Bert Roberta Summarization Cnn Dailymail

Developed by Ayham

A text summarization model fine-tuned on the CNN/DailyMail dataset based on BERT or RoBERTa architecture

Text Generation

Transformers

#News Summarization #BERT-RoBERTa Hybrid Architecture #Long Text Compression

Downloads 57

Release Time : 3/2/2022

Model Overview

This model is a text summarization model specifically designed for news article summarization tasks. It is based on the Transformer architecture (BERT or RoBERTa variants) and fine-tuned on the CNN/DailyMail dataset.

Model Features

News Summarization Optimization

Summarization capabilities specifically optimized for news article content

Transformer-based Architecture

Utilizes BERT or RoBERTa architecture with strong contextual understanding capabilities

Large-scale Dataset Training

Fine-tuned on the CNN/DailyMail dataset, containing a large number of news article samples

Model Capabilities

News article summarization

Long text compression

Key information extraction

Use Cases

News Media

Automatic News Summarization

Automatically generates concise summaries for lengthy news articles

Improves reader efficiency by quickly capturing key news points

Content Aggregation

News Digest Creation

Automatically generates summary content for daily news digests

Reduces manual editing workload

Property	Details
Model Type	Fine - tuned model on cnn_dailymail dataset
Training Data	cnn_dailymail

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Bert Roberta Summarization Cnn Dailymail

Model Overview

Model Features

Model Capabilities

Use Cases

🚀 bert_roberta_summarization_cnn_dailymail

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Model description

Intended uses & limitations

Training and evaluation data

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