# Multilingual semantic matching

This is a SentenceTransformer model fine-tuned from sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2, supporting multiple languages including Mongolian, capable of mapping text to a 384-dimensional vector space.

A sentence embedding model optimized for Ukrainian, based on the multilingual MPNet architecture, suitable for semantic similarity and feature extraction tasks

This is a multilingual sentence transformer model that maps text to a 384-dimensional vector space, suitable for semantic search and clustering tasks.

This is a Spanish sentence similarity model based on distiluse-base-multilingual-cased-v1, fine-tuned with the stsb_multi_mt dataset.

A Thai sentence embedding model based on mBERT, trained using the SimCSE method on Thai Wikipedia data, capable of mapping text to 768-dimensional vectors