# Multilingual vectorization

A vectorization tool developed by Sinequa that generates embedding vectors from input paragraphs or queries for sentence similarity calculation and retrieval tasks.

This is a model based on sentence-transformers that can map sentences and paragraphs into a 768-dimensional dense vector space, suitable for text similarity calculation and semantic search tasks in the e-commerce domain.

A multilingual vectorizer developed by Sinequa that generates embedding vectors for input paragraphs or queries, used for similarity calculation and information retrieval.

This is an Indonesian sentence embedding model based on sentence-transformers that maps text to a 768-dimensional vector space