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Tner Xlm Roberta Base Uncased Ontonotes5
This is an XLM-RoBERTa model fine-tuned for named entity recognition tasks, suitable for entity recognition in multilingual texts.
Downloads 605
Release Time : 3/2/2022
Model Overview
This model is based on the XLM-RoBERTa architecture, specifically fine-tuned for Named Entity Recognition (NER) tasks, capable of identifying various named entities in text.
Model Features
Multilingual Support
Based on the XLM-RoBERTa architecture, capable of processing multilingual texts
Efficient Entity Recognition
Optimized specifically for named entity recognition tasks, accurately identifying various entities in text
Pre-trained Model Fine-tuning
Fine-tuned on the XLM-RoBERTa pre-trained model, with strong language understanding capabilities
Model Capabilities
Text entity recognition
Multilingual text processing
Sequence labeling
Use Cases
Natural Language Processing
Information Extraction
Extracting entity information such as person names, locations, and organization names from unstructured text
Knowledge Graph Construction
Serving as a preliminary processing step for knowledge graph construction by identifying key entities in text
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