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Japanese Reranker Xsmall V2

Developed by hotchpotch
This is a very compact and fast Japanese reranking model, suitable for improving the accuracy of RAG systems.
Downloads 260
Release Time : 5/7/2025

Model Overview

This model is a Japanese reranking model primarily used to enhance the accuracy of Retrieval-Augmented Generation (RAG) systems, capable of running at practical speeds on CPUs or edge devices.

Model Features

Compact and Fast
Can run at practical speeds even in CPU or Apple Silicon environments
No Expensive GPU Required
Improves RAG system accuracy without requiring expensive GPU resources
Edge Device Friendly
Suitable for deployment on edge devices or in environments with low-latency requirements
Efficient Architecture
Optimized based on ModernBert's ruri-v3-pt-30m architecture

Model Capabilities

Text Relevance Scoring
Retrieval Result Reranking
Japanese Text Processing

Use Cases

Information Retrieval
Improving RAG System Accuracy
Reranking retrieval results in Retrieval-Augmented Generation systems
Significantly improves the relevance of retrieval results
Content Recommendation
Relevant Document Sorting
Sorting search results or recommended content by relevance
Improves user efficiency in accessing relevant information
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