# 32-dimensional Vector

This is a model based on sentence-transformers that maps sentences and paragraphs into a 32-dimensional dense vector space, suitable for tasks such as sentence similarity calculation, clustering, and semantic search.

A sentence similarity model based on sentence-transformers, mapping text to a 32-dimensional vector space

This is a sentence embedding model based on DistilBERT, capable of mapping sentences and paragraphs into a 32-dimensional dense vector space, suitable for tasks such as sentence similarity calculation, semantic search, and clustering.