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Ruri Base

Developed by cl-nagoya
Ruri is a universal text embedding model for Japanese, focusing on sentence similarity and feature extraction tasks.
Downloads 523.56k
Release Time : 8/28/2024

Model Overview

Ruri is a Japanese text embedding model based on the BERT architecture, primarily used for calculating sentence similarity and extracting text features. The model supports adding specific prefixes to query and passage texts for better performance.

Model Features

Japanese Optimization
Specially optimized for Japanese text, excelling in Japanese language tasks
Long Text Support
Supports sequences up to 512 tokens, capable of handling longer texts
High Performance
Outperforms other Japanese models in the JMTEB benchmark
Prefix Enhancement
Improves similarity calculation by adding query/passage prefixes

Model Capabilities

Sentence Similarity Calculation
Text Feature Extraction
Semantic Search
Text Clustering
Information Retrieval

Use Cases

Information Retrieval
Q&A System
Implements question-answering functionality by calculating similarity between queries and candidate answers
Achieved a score of 69.82 on JMTEB retrieval tasks
Text Analysis
Text Clustering
Automatically groups similar texts together
Achieved a score of 54.16 on JMTEB clustering tasks
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