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Text2vec Base Chinese Rag

Developed by Mike0307
A CoSENT framework model designed specifically for Chinese text semantic understanding, suitable for Retrieval Augmented Generation (RAG) tasks
Downloads 46.60k
Release Time : 4/15/2024

Model Overview

A Chinese text embedding model based on the CoSENT training framework, focusing on improving the semantic matching effect in Retrieval Augmented Generation (RAG) tasks

Model Features

Optimized for Chinese semantic understanding
Optimized specifically for the semantic matching needs of Chinese text
Adapted to RAG tasks
Embedding representation specifically designed for the retrieval augmented generation scenario
CoSENT framework
Adopts the advanced CoSENT training method to improve the sentence pair similarity calculation effect

Model Capabilities

Chinese text embedding representation
Semantic similarity calculation
Support for retrieval augmented generation

Use Cases

Information retrieval
Document retrieval
Find the document most semantically relevant to the query in the knowledge base
The example shows that the similarity score between the query and the relevant document reaches 0.7
Question answering system
RAG question answering
Used as a retrieval component in a retrieval augmented generation question answering system
Can accurately retrieve relevant document paragraphs containing the answer to the question
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