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Text2vec Base Chinese
A derivative model based on shibing624/text2vec-base-chinese, replacing MacBERT with LERT while keeping other training conditions unchanged, supporting Chinese text vectorization and sentence similarity calculation.
Downloads 1,613
Release Time : 3/7/2023
Model Overview
This model is a Chinese text vectorization model primarily used for feature extraction and sentence similarity calculation. It is an improved version of shibing624/text2vec-base-chinese, replacing the original MacBERT architecture with LERT while maintaining other training conditions.
Model Features
LERT Architecture
Replaces MacBERT in the original model with LERT, potentially offering better performance or efficiency.
ONNX Support
Provides an ONNX runtime version for easier deployment and inference across different platforms.
Chinese Optimization
Specifically optimized for Chinese text, suitable for Chinese natural language processing tasks.
Model Capabilities
Text vectorization
Feature extraction
Sentence similarity calculation
Use Cases
Natural Language Processing
Semantic Search
Can be used to build Chinese semantic search engines, matching relevant documents through vector similarity.
Q&A Systems
Used to calculate semantic similarity between questions and candidate answers.
Text Clustering
Implements automatic document classification and clustering through text vectorization.
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