Text embeddings are vector representations of words, sentences, paragraphs or documents that capture their semantic meaning. They serve as a core building block in many natural language processing (NLP) applications today, including information retrieval, question answering, semantic search and more. Recent advances in large language models (LLMs) like GPT-3 have shown impressive capabilities in few-shot […] The post Training Improved Text Embeddings with Large Language Models appeared first on Unite.AI.