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Bart Large Scientific Lay Summarisation

Developed by sambydlo
A text summarization model based on the BART-large architecture, specifically designed for generating lay summaries of scientific literature.
Downloads 66
Release Time : 3/28/2023

Model Overview

This model is trained using Amazon SageMaker and Hugging Face deep learning containers, capable of converting complex scientific literature into easily understandable lay summaries.

Model Features

Scientific literature simplification
Specifically designed for scientific literature, it can transform professional content into summaries understandable by the general public
High-performance summarization
Achieves a ROUGE-1 score of 42.621 on the PLOS dataset, demonstrating excellent performance
SageMaker optimization
Trained using Amazon SageMaker and Hugging Face containers, suitable for cloud deployment

Model Capabilities

Scientific text summarization
Content simplification
Technical term conversion

Use Cases

Academic dissemination
Lay summary of research papers
Converts professional research papers into brief summaries understandable by the media or non-specialists
ROUGE-1 score of 41.3174, maintaining the core content of the original while improving readability
Science communication
Science news generation
Automatically generates science news articles based on research papers
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