A Catalog of Google's T5 series LLMs

Google's T5 is a versatile text-to-text model that can perform a wide range of language tasks, while their later introduced FLAN (Few-shot Language Adaptation Network) strategy was designed to enhance pretrained LLMs zero-shot performance on unseen task by further instruction finetuning produced optimized models of their base models as FLAN-T5, FLAN-PaLM, and FLAN-LAMDA. This comparison showcases this development based on the central characteristics of the models.

谷歌T5是一款通用的文本到文本模型，可完成广泛的语言任务。其后续推出的FLAN（少样本语言适配网络，Few-shot Language Adaptation Network）策略，旨在通过进一步的指令微调对基础预训练大语言模型（Large Language Model，LLM）进行优化，以提升其在未见任务上的零样本（Zero-shot）表现，由此衍生出FLAN-T5、FLAN-PaLM以及FLAN-LAMDA等优化模型。本次对比将围绕这些模型的核心特征，展示这一技术发展脉络。