Pretraining Llms
The foundational step in developing large language models (LLMs), where the model is trained on a vast and diverse dataset, typically sourced from the internet. This extensive training equips the model with a comprehensive grasp of language, encompassing grammar, world knowledge, and rudimentary reasoning.
Areas of application
- Natural Language Processing
- Chatbots and Conversational AI
- Text Generation and Summarization
- Question Answering and Dialogue Systems
- Language Translation and Adaptation
- Content Creation and Generation
Example
Pretraining a LLM on a dataset of books would enable it to generate coherent and contextually appropriate text, such as summarizing a chapter or generating a short story in the same style as the training data.