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Led Pubmed Sumpubmed 1
L
Led Pubmed Sumpubmed 1
Developed by Blaise-g
This is a biomedical paper abstract generation model based on the LED architecture, specifically optimized for PubMed literature.
Text Generation
Transformers Supports Multiple Languages#Biomedical Abstract Generation#High ROUGE-1 Score#Long Text Processing
Transformers Downloads 13
Release Time : 7/29/2022
Model Overview
The model uses the LED (Longformer-Encoder-Decoder) architecture, specifically designed for generating concise and accurate abstracts from PubMed biomedical papers.
Model Features
Biomedical Domain Optimization
Specifically trained and optimized for PubMed biomedical literature
Long Text Processing Capability
Based on the LED architecture, suitable for long document abstract generation
High-Quality Abstracts
Performs exceptionally well on PubMed datasets, achieving a ROUGE-1 score of 45.861
Model Capabilities
Biomedical Text Abstract Generation
Long Document Processing
English Text Understanding and Generation
Use Cases
Academic Research
Rapid Reading of Biomedical Literature
Generates concise abstracts of PubMed papers for researchers, improving literature reading efficiency
ROUGE-1 score of 45.861, indicating good abstract quality
Knowledge Management
Medical Knowledge Base Construction
Automatically processes large volumes of biomedical literature to generate structured abstracts for knowledge bases
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