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Albert Base Chinese Ner
Provides transformers models and natural language processing tools for Traditional Chinese
Downloads 2,548
Release Time : 3/2/2022
Model Overview
This project offers Chinese natural language processing models based on the ALBERT architecture, including word segmentation, part-of-speech tagging, named entity recognition, and other functionalities, specifically optimized for Traditional Chinese.
Model Features
Traditional Chinese Optimization
Specifically optimized for Traditional Chinese text processing
Multi-functional NLP Tool
Integrates various natural language processing functions such as word segmentation, part-of-speech tagging, and named entity recognition
Based on ALBERT Architecture
Utilizes the efficient ALBERT model architecture, reducing parameter count while maintaining performance
Model Capabilities
Chinese Word Segmentation
Part-of-Speech Tagging
Named Entity Recognition
Text Processing
Use Cases
Text Analysis
Chinese Text Preprocessing
Performs word segmentation and part-of-speech tagging on Traditional Chinese text
Provides structured text data for downstream NLP tasks
Entity Recognition Applications
Identifies named entities such as person names, locations, and organizations from Chinese text
Can be used for information extraction, knowledge graph construction, and other scenarios
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