Part 2: Mastering LLM Development
In this part, you will learn about data, how to set up your training environment, hyperparameter tuning, and challenges in training LLMs. You will also learn about advanced training strategies, which entail transfer learning and fine-tuning, as well as curriculum learning, multitasking, and continual learning models. Instruction on fine-tuning LLMs for specific applications is also included; here, you will learn about the needs of NLP applications, tailoring LLMs for chatbots and conversational agents, customizing models for language translation, and fine-tuning for nuanced understanding. Finally, we will focus on testing and evaluation, which includes learning about metrics for measuring LLM performance, how to set up rigorous testing protocols, human-in-the-loop instances, ethical considerations, and bias mitigation.
This part contains the following chapters:
- Chapter 3, The Mechanics of Training LLMs
- Chapter 4, Advanced Training Strategies...
