U

USER Bge M3

Developed by deepvk
Russian universal sentence encoder, based on the sentence-transformers framework, specifically designed to extract 1024-dimensional dense vectors for Russian text
Downloads 339.46k
Release Time : 7/5/2024

Model Overview

This model maps Russian sentences and paragraphs to a 1024-dimensional dense vector space, suitable for tasks such as clustering or semantic search. Optimized for Russian language processing based on the bge-m3 model architecture.

Model Features

Russian language optimization
Specially optimized and trained for Russian text, excelling in Russian semantic understanding tasks
Multi-dataset training
Trained on multiple Russian datasets including ru-HNP and ru-WANLI
High-performance vector encoding
Generates 1024-dimensional dense vectors, supporting efficient similarity calculation and clustering analysis

Model Capabilities

Russian text vectorization
Semantic similarity calculation
Text clustering analysis
Feature extraction

Use Cases

Information retrieval
Russian semantic search
Building semantic matching functionality for Russian search engines
Average score of 0.799 on the encodechka benchmark
Text analysis
Russian text clustering
Topic clustering for Russian news or social media content
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