mlfoundations-dev/instruction_filtering_scale_up_code_base_embedding_filter_mean

该数据集包含了一系列特征，如指令种子、来源、推理、解决方案等，并划分为训练集。数据集主要用于存储和训练与对话相关的模型，其中包含了对话双方的标识和对话内容。每个样本还包含了评分信息，可能用于评估对话质量或模型性能。

The dataset includes features such as instruction seeds, sources, reasoning, solutions, and is split into a training set. It is primarily used for storing and training conversation-related models, containing identifiers for both sides of the conversation and the content of the conversation. Each sample also includes scoring information, which may be used to evaluate the quality of conversations or the performance of models.