This specialization 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, and 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.
What you'll learn
understand how to build and deploy large language models
fine-tune a Llama 3 model using reinforcement learning from human feedback (RLHF)
create recommendation engines using Siamese BERT architectures
implement an information retrieval system with OpenAI embeddings and GPT-4
develop an image captioning system leveraging vision transformers and GPT