Today's paper introduces Instruction Pre-Training, a new approach to pre-training language models using supervised multitask learning. Instead of training only on raw text corpora, this method augments the pre-training data with instruction-response pairs generated by an instruction synthesizer. This allows the model to learn from diverse tasks during pre-training, enhancing its generalization abilities.
Instruction Pre-Training utilizes supervised multitask learning. Unlike traditional training that solely relies on raw text corpora, this approach augments the pre-training data with instruction-response pairs generated by an instruction synthesizer. This enables the model to learn from a variety of tasks during pre-training, thereby enhancing its generalization capabilities.
Instruction Pre-Training utilizes supervised multitask learning. Unlike traditional training that solely relies on raw text corpora, this approach augments the pre-training data with instruction-response pairs generated by an instruction synthesizer. This enables the model to learn from a variety of tasks during pre-training, thereby enhancing its generalization capabilities.