# High-precision Matching

This is a sentence transformer model fine-tuned based on BAAI/bge-base-en-v1.5, specifically optimized for Q&A systems related to 3GPP technical documents, capable of mapping text to a 768-dimensional vector space.

An optimized sentence transformer model based on nomic-embed-text-v2-moe, specializing in sentence similarity calculation and feature extraction for Russian legal texts

A CLIP-based fine-tuned model for LEGO brick image-text matching, specifically designed to recognize LEGO bricks and their descriptions.

A financial domain sentence embedding model fine-tuned based on BAAI/bge-m3, supporting 1024-dimensional vector representation, suitable for semantic similarity and information retrieval tasks

Dutch Q&A model fine-tuned from Google's multilingual BERT, trained on translated SQuAD2.0 dataset