ryoungj/bootstrap-latent-thought-data

这是一个用于预训练语言模型的数据集，专注于通过建模和推断文本生成过程中的潜在思维来提高数据效率。数据集包含数学问题相关的文本，以及用于推理、自我改进和潜在变量建模的特征。数据集采用了期望最大化算法来优化模型生成的思维和数据效率。

This dataset is for pretraining language models, focusing on improving data efficiency by modeling and inferring latent thoughts underlying the text generation process. It includes text related to mathematical problems, as well as features for reasoning, self-improvement, and latent variable modeling. The dataset utilizes an expectation-maximization algorithm to optimize the models generated thoughts and data efficiency.