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Distilbert Base Uncased Finetuned Squad
A question-answering model based on DistilBERT, fine-tuned on the SQuAD dataset for extractive question answering tasks.
Downloads 16
Release Time : 6/27/2022
Model Overview
This model is a lightweight question-answering model based on DistilBERT, fine-tuned on the SQuAD dataset, excelling at extracting answers from given texts.
Model Features
Lightweight and Efficient
Based on DistilBERT architecture, it is 40% smaller than the original BERT model while retaining 95% of its performance.
Accurate Question Answering
Fine-tuned on the SQuAD dataset, it can accurately extract answers from texts.
Fast Inference
The distilled model design enables faster inference speed compared to the full BERT model.
Model Capabilities
Text Understanding
Answer Extraction
Context Analysis
Use Cases
Customer Support
Automated Q&A System
Used to build customer support systems that can automatically answer user questions.
Can accurately extract relevant answers from knowledge bases
Educational Technology
Learning Assistant Tool
Helps students quickly find answers to questions from textbooks.
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