Chinese Bert Wwm
A Chinese pre-trained BERT model using whole word masking strategy, designed to accelerate Chinese natural language processing research.
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Release Time : 3/2/2022
Model Overview
This is a Chinese pre-trained BERT model based on the whole word masking strategy, optimized specifically for Chinese natural language processing tasks, capable of better handling semantic understanding tasks for Chinese text.
Model Features
Whole Word Masking Strategy
Uses whole word masking instead of character-level masking, better suited for Chinese language characteristics, enhancing the model's understanding of Chinese text.
Chinese Optimization
Specifically optimized for Chinese text, suitable for various Chinese natural language processing tasks.
Pre-trained Model
Provides pre-trained model weights that users can directly apply to downstream tasks or fine-tune.
Model Capabilities
Text Classification
Named Entity Recognition
Question Answering System
Semantic Understanding
Use Cases
Natural Language Processing
Chinese Text Classification
Used for classifying Chinese text, such as news categorization, sentiment analysis, etc.
Named Entity Recognition
Identifies named entities in Chinese text, such as person names, place names, organization names, etc.
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