Large Language Models

Large Language Models (LLMs) are a type of artificial intelligence model based on deep learning architectures, particularly transformers, that are trained on vast amounts of text data to understand, generate, and manipulate human language. They can perform a wide range of natural language processing tasks such as text generation, translation, summarization, and question-answering. These models have billions or trillions of parameters, enabling them to capture complex linguistic patterns and context.

Also known as: LLMs, Large Language Model, Transformer Models, Foundation Models, Generative AI Models

Why learn Large Language Models?

Developers should learn about LLMs to build applications involving natural language understanding, such as chatbots, content creation tools, and automated customer support systems. They are essential for tasks requiring advanced text processing, like sentiment analysis, code generation, and data extraction from unstructured text, making them valuable in fields like AI research, software development, and data science.

Learning Resources

• docs: Hugging Face Transformers Documentation
• course: Stanford CS224N: Natural Language Processing with Deep Learning
• tutorial: Andrej Karpathy's Neural Networks: Zero to Hero
• docs: Attention Is All You Need Paper