# 768-dimensional Vector Space

An embedding model specifically designed for Vietnamese, optimized based on PhoBERT, capable of encoding Vietnamese sentences into a 768-dimensional vector space, suitable for various scenarios such as semantic search and text clustering.

This is a Nepali sentence similarity calculation model based on sentence-transformers, which maps sentences and paragraphs into a 768-dimensional vector space.

A sentence transformation model based on RoBERTa-large, specifically designed for sentence similarity tasks, trained on ANLI, MNLI, and SNLI datasets

This is a Spanish sentence similarity calculation model based on sentence-transformers, capable of mapping sentences and paragraphs into a 768-dimensional vector space.