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Albert Base Chinese
A Traditional Chinese Transformer model developed by the Lexical Knowledge Base Group of Academia Sinica, including architectures such as ALBERT, BERT, GPT2 and natural language processing tools
Downloads 280
Release Time : 3/2/2022
Model Overview
Provides Traditional Chinese Transformer models and natural language processing tools, including functions such as word segmentation, part-of-speech tagging, and named entity recognition
Model Features
Traditional Chinese support
A natural language processing model specifically optimized for Traditional Chinese
Multi-task processing
Integrates multiple NLP functions such as word segmentation, part-of-speech tagging, and named entity recognition
Efficient architecture
Adopts the ALBERT architecture, which is lighter and more efficient than traditional BERT models
Model Capabilities
Chinese word segmentation
Part-of-speech tagging
Named entity recognition
Text feature extraction
Use Cases
Text processing
Chinese text analysis
Perform word segmentation and part-of-speech tagging on Traditional Chinese texts
Accurately identify word boundaries and part-of-speech categories
Named entity recognition
Identify entities such as person names, place names, and organization names from Chinese texts
Extract key entity information
Academic research
Linguistic analysis
Used for grammatical analysis in Chinese linguistic research
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