Natural Language Processing
Behavioral Benchmarking of LLMs
In this course, you’ll experiment with deeper aspects of LLM evaluation: token usage efficiency, temperature sensitivity, model output consistency, and detecting hallucinations. Through lightweight API experiments, you’ll develop intuition for how models behave beyond accuracy scores.
OpenAI
Python
4 lessons
13 practices
1 hour
Badge for Large Language Models,
Course details
Measuring and Interpreting Token Usage in LLMs
Comparing Token Counts to Prompt and Answer Lengths
Exploring Prompt Length and Token Usage
Refactoring Token Usage for Cleaner Code
Previous
Turn screen time into skills time
Practice anytime, anywhere with our mobile app.
Download on the App StoreGet it on Google Play
Sign up
Join the 1M+ learners on CodeSignal
Be a part of our community of 1M+ users who develop and demonstrate their skills on CodeSignal