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Bart Base Few Shot K 128 Finetuned Squad Seed 4
B
Bart Base Few Shot K 128 Finetuned Squad Seed 4
Developed by anas-awadalla
A question-answering model based on the BART-base architecture, fine-tuned on the SQuAD dataset, suitable for reading comprehension tasks.
Downloads 13
Release Time : 9/30/2022
Model Overview
This model is a version based on the BART-base architecture, fine-tuned on the SQuAD dataset, primarily used for question answering and reading comprehension tasks.
Model Features
Based on BART architecture
Utilizes the BART-base architecture, combining the advantages of bidirectional encoders and autoregressive decoders.
SQuAD fine-tuning
Fine-tuned on the SQuAD dataset to optimize performance for question-answering tasks.
Few-shot learning
Supports few-shot learning, adapting to scenarios with limited annotated data.
Model Capabilities
Question answering generation
Reading comprehension
Text understanding
Use Cases
Education
Automated answer system
Used to build automated answer systems in the education sector, helping students understand article content.
Customer service
Intelligent customer service
Used to build intelligent customer service systems that automatically answer user questions based on documents.
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