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Chinese Lert Base
LERT is a linguistics theory-driven pre-trained language model designed to enhance performance by incorporating linguistic knowledge.
Downloads 306
Release Time : 10/26/2022
Model Overview
LERT is a pre-trained language model that improves performance in natural language processing tasks by integrating linguistic knowledge. It is driven by linguistic theories and aims to better understand and generate natural language.
Model Features
Linguistics Theory-driven
The model enhances performance by incorporating linguistic knowledge, making it excel in natural language processing tasks.
Pre-trained Model
Pre-trained on large-scale corpora to capture rich linguistic features.
Chinese Support
Optimized specifically for Chinese language characteristics, suitable for Chinese natural language processing tasks.
Model Capabilities
Text classification
Named entity recognition
Natural language understanding
Natural language generation
Use Cases
Natural Language Processing
Chinese Text Classification
Used for classifying Chinese texts, such as sentiment analysis, topic classification, etc.
Named Entity Recognition
Used to identify named entities in Chinese texts, such as person names, locations, organization names, etc.
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