Distilbert Base Multilingual Cased Ner Hrl
A named entity recognition model for 10 high-resource languages, based on a fine-tuned Distil BERT base model, capable of identifying three types of entities: locations, organizations, and persons.
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Release Time : 3/2/2022
Model Overview
This model is a fine-tuned DistilBERT model on aggregated data from 10 high-resource languages, specifically designed for named entity recognition tasks, supporting the identification of LOC, ORG, and PER entity types.
Model Features
Multilingual Support
Supports named entity recognition in 10 high-resource languages, including Arabic, Chinese, and more.
Lightweight Model
Based on the DistilBERT architecture, it is more lightweight compared to the original BERT model while maintaining high performance.
Entity Type Recognition
Accurately identifies three types of entities: locations (LOC), organizations (ORG), and persons (PER).
Model Capabilities
Multilingual text processing
Named entity recognition
Sequence labeling
Use Cases
Information Extraction
News Article Entity Extraction
Extracts key entity information such as persons, organizations, and locations from multilingual news articles.
Accurately identifies named entities and their types in the text
Text Analysis
Multilingual Document Processing
Processes documents containing multiple languages to extract key entity information.
Supports entity recognition in 10 languages
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