Fine-Tuning LLMs for Specific Applications
In this chapter, we’ll focus on the versatility of LLMs and specify fine-tuning techniques tailored to a variety of NLP tasks. From the intricacies of conversational AI to the precision required for language translation and the subtleties of sentiment analysis, you’ll learn how to customize LLMs for nuanced language comprehension and interaction, equipping them with the skills they need to meet specific application needs.
In this chapter, we’re going to cover the following main topics:
- Incorporating LoRA and PEFT for efficient fine-tuning
- Understanding the needs of NLP applications
- Tailoring LLMs for chatbots and conversational agents
- Customizing LLMs for language translation
- Sentiment analysis and beyond – fine-tuning for nuanced understanding
By the end of this chapter, you should be able to understand how to augment the adaptability of LLMs for a variety of NLP tasks, with a...
