Testing Solutions Based on Large Language Models
摘要
Large language models (LLMs) are ML models trained on extensive data corpora, enabling them to perform multiple downstream ML tasks. Consequently, using LLMs allows the ML solution developer to jumpstart the solution construction by starting with one or more LLMs. This chapter discusses the testing of solutions based on LLMs, outlining several relevant characteristics of LLM-based solution construction and addressing unique challenges in their testing.