concept

Pre-trained Language Models

Pre-trained language models are AI models trained on vast amounts of text data to understand and generate human language, using techniques like self-supervised learning. They serve as a foundation for various natural language processing tasks, such as text classification, translation, and question-answering, by learning general linguistic patterns before being fine-tuned for specific applications.

Also known as: PLMs, Pretrained Language Models, Pre-trained NLP Models, Foundation Models, Large Language Models (LLMs)

🧊Why learn Pre-trained Language Models?

Developers should learn about pre-trained language models when working on NLP projects that require high accuracy with limited labeled data, as they reduce training time and computational costs. They are essential for applications like chatbots, sentiment analysis, and content generation, enabling rapid deployment of language-aware systems.