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Distilbert Base Uncased Finetuned Ner
A lightweight model fine-tuned on the NER task based on the DistilBERT-base-uncased model
Downloads 15
Release Time : 3/2/2022
Model Overview
This model is a lightweight version of DistilBERT, fine-tuned for Named Entity Recognition (NER) tasks, suitable for entity recognition in English text
Model Features
Lightweight Architecture
Based on the DistilBERT architecture, it is smaller and faster than the standard BERT model while maintaining good performance
NER Task Optimization
Specially fine-tuned for Named Entity Recognition tasks, suitable for entity extraction applications
Model Capabilities
Text Entity Recognition
Named Entity Extraction
Use Cases
Information Extraction
News Entity Extraction
Extract entities such as person names, locations, and organization names from news text
Document Analysis
Process professional term recognition in legal or medical documents
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