Distilbert Base Uncased Finetuned Ner Final
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Distilbert Base Uncased Finetuned Ner Final
Developed by Lilya
A lightweight Named Entity Recognition (NER) model based on the DistilBERT architecture, fine-tuned for specific tasks
Downloads 15
Release Time : 4/27/2022
Model Overview
This model is a lightweight version based on the DistilBERT architecture, specifically fine-tuned for Named Entity Recognition tasks. It inherits the efficiency of DistilBERT while being optimized for NER tasks.
Model Features
Lightweight and Efficient
Based on the DistilBERT architecture, it is smaller and faster than standard BERT models while maintaining good performance
Task-Specific Optimization
Specifically fine-tuned for Named Entity Recognition tasks
English Language Support
Focused on entity recognition for English text
Model Capabilities
Text Entity Recognition
Named Entity Classification
Sequence Labeling
Use Cases
Information Extraction
News Entity Extraction
Identify entities such as people, places, and organizations from news articles
Document Analysis
Automatically label key entity information in documents
Knowledge Graph Construction
Knowledge Graph Entity Extraction
Extract entities from text for building knowledge graphs
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