Instruction Pre-Training of Language models using Monster-API

Pre-training is an essential step in developing large-scale language models, providing a foundation for their understanding and generation capabilities. This process involves training the model on extensive datasets containing diverse text sources using self-supervised learning techniques like masked language modeling or autoregressive language modeling. The goal of pre-training is not to solve specific tasks but to imbue the model with broad knowledge of language structure, enabling it to generalize effectively when fine-tuned for specific applications. Instruction pre-training is a novel method that augments the unsupervised training corpus with instructions to enhance model performance and has proven effective in domain-adaptive fine-tuning. Monster API allows users to convert their unlabeled corpus into instruction-augmented pre-training corpora suitable for pre-training, making it a valuable tool for developers facing hardware limitations and budget constraints.