# Text Semantic Similarity

LLM2Vec is a simple method to convert decoder-only large language models into text encoders by enabling bidirectional attention, masked next-token prediction, and unsupervised contrastive learning.

INSTRUCTOR is a text embedding model based on the T5 architecture, focusing on sentence similarity calculation and information retrieval tasks. It excels in various NLP tasks, including text classification, clustering, and semantic similarity evaluation.

A text embedding model based on the T5 architecture, focusing on sentence similarity calculation and text retrieval tasks, with excellent performance in multiple benchmark tests.