Fine-tuning datasets for h2oGPT models

该数据集精心筛选了用于训练参数量从70亿到400亿的大型语言模型的微调数据。它还包括了高效的微调代码、提示工程，以及一个无需编码的微调框架（H2O LLM Studio）。任务的目的是对大型语言模型进行微调。

This dataset is carefully curated to provide fine-tuning data for large language models with parameter sizes ranging from 7 billion to 40 billion. It also includes efficient fine-tuning code, prompt engineering techniques, and a no-code fine-tuning framework, H2O LLM Studio. The objective of this dataset is to facilitate the fine-tuning of large language models.