# Dense vector representation

This is a sentence transformer model fine - tuned from sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2, which can map text to a 384 - dimensional vector space for tasks such as semantic similarity calculation.

This is a Korean sentence embedding model trained on KLUE/NLI and KLUE/STS datasets, utilizing the sentence-transformers framework and optimized for sentence similarity tasks through two-stage training.

A dual-tower network model trained for zero-shot and few-shot text classification, supporting multilingual sentence embedding