Large Language Models (Llms)
Created: 2023-05-26 17:42
#note
A large language model is a type of DL models that is designed to understand and generate human language. It is trained on massive amounts of text data to learn the patterns, relationships, and context of language. These models use deep learning techniques, such as neural networks with multiple layers, to process and generate human-like text.
Large language models have the ability to generate coherent and contextually relevant responses to prompts or queries. They can understand and generate text in various languages and are capable of tasks like language translation, text completion, summarization, question answering, and more.
One of the notable examples of a large language model is OpenAI's GPT (Generative Pre-trained Transformer) series, such as GPT-3 (which stands for "Generative Pre-trained Transformer 3"). GPT-3 has been trained on a diverse range of internet text and has shown impressive capabilities in understanding and generating human-like text across a wide array of applications.
Large language models have the potential to revolutionize natural language processing tasks, improve human-computer interactions, and assist in various language-related applications in fields like customer support, content generation, language translation, and more.
For an overview of how LLMs are trained and aligned after pretraining, see LLM Training and Alignment Evolution, which covers the evolution from RLHF - Reinforcement Learning from Human Feedback through DPO - Direct Preference Optimization to RLVF - Reinforcement Learning from Verifiable Feedback. Fine-tuning approaches include PEFT - Parameter-Efficient Fine-Tuning, LoRA - Low-Rank Adaptation of LLMs, and Instruction Tuning for Large Language Models- A Survey.