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Distilbart Multi News 12 6 2
DistilBART-CNN-12-6 is a lightweight summarization generation model based on the BART architecture, specifically optimized for the CNN/Daily Mail dataset.
Downloads 313
Release Time : 4/20/2025
Model Overview
This model is a distilled version of the BART model, focusing on text summarization tasks, capable of extracting key information from long texts to generate concise summaries.
Model Features
Lightweight and efficient
Retains 97% of the BART model's performance through knowledge distillation while reducing the parameter count by half
CNN/Daily Mail optimization
Specifically optimized for news summarization scenarios
Fast inference
Significantly improved inference speed compared to the full BART model
Model Capabilities
Text summarization generation
Long text comprehension
Key information extraction
Use Cases
News media
Automatic news summarization
Generates concise summaries for lengthy news reports
Produces news summaries that conform to human writing habits
Content analysis
Research report summarization
Extracts core findings from academic papers or technical reports
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