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Bart Base Finetuned Cnn
A pre-trained model based on the BART architecture, specifically designed for text summarization tasks of English news articles.
Downloads 20
Release Time : 2/13/2025
Model Overview
This model is based on the BART-base architecture and fine-tuned on the CNN/Daily Mail dataset, capable of generating concise summaries for news articles.
Model Features
Sequence-to-Sequence Architecture
Utilizes a Transformer architecture with a bidirectional encoder and auto-regressive decoder, suitable for generation tasks.
News Summarization Optimization
Fine-tuned on the CNN/Daily Mail dataset, specifically optimized for news article summarization tasks.
Efficient Generation
Capable of generating concise summaries while maintaining semantic coherence.
Model Capabilities
Text Summarization Generation
News Content Compression
Key Information Extraction
Use Cases
News Media
News Digest Generation
Automatically generates brief summaries of news articles for news aggregation or push services.
Produces summaries that match human writing style, with good ROUGE scores.
Content Preview
Generates preview summaries for long articles to help readers quickly grasp the content.
Extracts key information points while preserving the main meaning of the original text.
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