R

Roberta Large NER

Developed by 51la5
Named entity recognition model fine-tuned on the English CoNLL-2003 dataset based on the XLM-RoBERTa-large model
Downloads 60.39k
Release Time : 10/17/2022

Model Overview

This model is an English fine-tuned version of the multilingual pre-trained model XLM-RoBERTa, specifically designed for named entity recognition tasks, capable of identifying entities such as person names, place names, and organization names in text

Model Features

Multilingual pre-training foundation
Based on the XLM-RoBERTa-large model supporting 100 languages, with strong cross-lingual representation capabilities
Domain-specific optimization
Fine-tuned on the standard NER dataset CoNLL-2003, optimized for named entity recognition tasks
High accuracy
Performs excellently on standard test sets, accurately identifying various named entities

Model Capabilities

Named entity recognition
Text token classification
English text processing

Use Cases

Information extraction
News entity extraction
Extract key information such as person names, place names, and organization names from news articles
Accurately identifies various entities in text
Document automation processing
Automatically process named entities in legal or medical documents
Improves document processing efficiency
Knowledge graph construction
Knowledge graph entity extraction
Extract entities from unstructured text for knowledge graph construction
Provides structured data for knowledge graphs
Featured Recommended AI Models
AIbase
Empowering the Future, Your AI Solution Knowledge Base
© 2025AIbase