# 384-dimensional vector embedding

This is an Italian sentence embedding model based on sentence-transformers, capable of mapping sentences and paragraphs into a 384-dimensional dense vector space, suitable for tasks such as semantic search and sentence similarity calculation.

This is a sentence transformer model based on the MiniLM-L6 architecture, capable of mapping text to a 384-dimensional vector space, suitable for semantic search and text similarity calculation tasks.