# Dense vector embedding

Tooka-SBERT-V2-Small is a trained sentence transformer model for semantic text similarity and embedding tasks. It can map sentences and paragraphs to a dense vector space where semantically similar texts are close to each other.

This is a model trained based on sentence-transformers, capable of mapping sentences and paragraphs into a 768-dimensional dense vector space, suitable for various tasks such as semantic text similarity calculation and semantic search.