# Russian sentence embeddings

Russian universal sentence encoder, based on the sentence-transformers framework, specifically designed to extract 1024-dimensional dense vectors for Russian text

BERT model for computing Russian sentence embeddings, developed based on cointegrated/LaBSE-en-ru with optimized Russian language processing performance

A Russian sentence encoder model based on the RoPEBert architecture, supporting a context length of 2048 tokens and excelling in the encodechka benchmark tests.

This is a Russian sentence embedding model based on PyTorch and Transformers, supporting multi-task processing and capable of generating high-quality sentence vector representations.

A compact BERT-based Russian encoder capable of generating high-quality sentence embeddings

This is a large Russian language model based on the BERT architecture, specifically designed for generating sentence embeddings with case-insensitive processing support.