Scoring LLM Outputs with Logprobs and Perplexity

In this course, you'll explore how to evaluate the fluency and likelihood of LLM outputs using internal scoring signals like log probabilities and perplexity. You'll work with OpenAI's completion models to analyze how models "think" under the hood. This course builds naturally on the first two by focusing on model-internal evaluation instead of external references.