LLaMA-2

该数据集涵盖了LLaMA-2模型系列，这一系列包含了多种规模的大型语言模型，参数量从70亿到700亿不等，主要用于强化学习从人类反馈（RLHF）的实验。目前，LLaMA-2模型是应用最广泛的开放源代码大型语言模型，其模型规模包括7B、13B、34B和70B参数，针对的任务是强化学习从人类反馈。

This dataset covers the LLaMA-2 model family, which comprises large language models with parameter sizes ranging from 7 billion to 70 billion, available in four specific scales: 7B, 13B, 34B, and 70B. These models are primarily utilized for experiments on Reinforcement Learning from Human Feedback (RLHF). Currently, the LLaMA-2 model family is among the most widely adopted open-source large language models, with its targeted task being Reinforcement Learning from Human Feedback.