Evaluation Techniques for Large Language Models

Explore practical tools and best practices for evaluating and choosing Large Language Models (LLMs) in this comprehensive tutorial presented by Rajiv Shah, Machine Learning Engineer at Hugging Face. Gain insights into the capabilities of LLMs compared to traditional ML models and learn various evaluation techniques, including evaluation suites, head-to-head competition approaches, and using LLMs to evaluate other LLMs. Delve into the subtle factors affecting evaluation, such as the role of prompts, tokenization, and requirements for factual accuracy. Examine model bias and ethical considerations through working examples. Acquire an in-depth understanding of LLM evaluation tradeoffs and methods, with reusable code provided in Jupyter Notebooks for each technique discussed.

Evaluation Techniques for Large Language Models