pretraining data. For example, PaLM [22] and BLOOM [92] excel in multilingual tasks and machine translation with an
abundance of multilingual pretraining data. Moreover, PaLM’s performance in Question Answering tasks is enhanced
by incorporating a considerable amount of social media conversations and Books corpus [22]. Likewise, code execution
and code completion capabilities of GPT-3.5 (code-davinci-002) are amplified by the integration of code data in its
pretraining dataset. In brief, when selecting LLMs for downstream tasks, it is advisable to choose the model pre-trained
on a similar field of data.
Harnessing the Power of LLMs in Practice- A Survey on ChatGPT and Beyond