This course capitalizes on the latest advancements in Large Language Models (LLMs) like FLAN-T5, enabling professionals to harness these tools effectively in the rapidly-evolving AI landscape. Instructor Axel Sirota helps you establish a strong foundation in the basics of LLMs, exploring their architecture, evolution, and role in the current AI landscape. Delve into prompt engineering and learn how to craft effective prompts that guide LLM outputs for specific tasks. Then deep dive into transfer learning and PEFT fine-tuning using LoRA and find out how to adapt and optimize LLMs for varied NLP tasks. Each course section comprises live-action clips, slides, and demos, as well as real-world challenges covering prompt engineering, transfer learning, and fine-tuning techniques to enhance FLAN-T5's capabilities. Plus, you'll complete a final project focused on building an NLP solution encompassing sentiment analysis, text summarization, and question answering.

https://rapidgator.net/file/df65ce93292cb6c27b9c6d3575734b56/Fine-Tuning_for_LLMs_from_Beginner_to_Advanced.rar.html