Quick Start Guide to Large Language Models (LLMs)- ChatGPT, Llama, Embeddings, Fine-Tuning, and Multimodal AI

This video is a quick start guide to help people use and launch LLMs like GPT, Llama, T5, and BERT at scale. It presents a step-by-step approach to building and deploying LLMs, with real-world case studies to illustrate the concepts. The video covers topics such as constructing agents, fine-tuning a Llama 3 model with RLHF, building recommendation engines with Siamese BERT architectures, launching an information retrieval system with OpenAI embeddings and GPT-4, and building an image captioning system with the vision transformer and GPT. This guide provides clear instructions and best practices for using LLMs and will be a valuable resource for anyone looking to use LLMs in their projects.

Large language models (LLMs) are a type of artificial intelligence (AI) that use deep learning to process natural language. LLMs are trained on large datasets of text and can be used to generate text, answer questions, and perform other tasks related to natural language processing.