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En Finetuned Squad Qa Minilmv2 32

Developed by subhasisj
MiniLMv2 Q&A model fine-tuned on SQuAD dataset for English reading comprehension tasks
Downloads 18
Release Time : 5/13/2022

Model Overview

This model is a Q&A model based on the MiniLMv2 architecture, fine-tuned on the SQuAD dataset, specifically designed to answer questions based on given text.

Model Features

Efficient Q&A
Optimized for the SQuAD dataset, capable of efficiently and accurately answering text-based questions
Lightweight architecture
Based on MiniLMv2 architecture, reducing model size while maintaining performance
Transfer learning
Leverages large-scale language representations through pre-training and fine-tuning processes

Model Capabilities

Text understanding
Question answering
Context analysis

Use Cases

Education
Reading comprehension assistance
Helps students understand article content and answer questions
Improves reading comprehension efficiency
Information retrieval
Document Q&A system
Quickly extracts answers to questions from documents
Improves information retrieval efficiency
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