Large Language Models (LLMs) have great potential for speeding up the development of text-based applications, such as chatbots and question-answering interfaces. To use LLMs effectively, fine-tuning is critical. Fine-tuning involves introducing the LLM to new or updated data to customize its performance according to your requirements, including improving accuracy on core topics, enhancing coverage of unique cases, reducing bias and harmful content, and more.

Yet, fine-tuning an LLM is a challenging task! In this webinar, we will cover:

• Why you may need to fine-tune LLMs
• What are the fundamental tasks involved in fine-tuning
• A real-life example of two fine-tuning use cases from our customers

You will also get access to a notebook that enables you to fine-tune an LLM for domain-specific needs.

Join us!