This is a modified version of run_gpt4o.py from TIGER-AI-Lab/MMLU-Pro, and it lets you run MMLU-Pro benchmark via the OpenAI Chat Completion API. It's tested on Ollama and Llama.cpp, but it should also work with LMStudio, Koboldcpp, Oobabooga with openai extension, etc.
I kept the testing method exactly the same as the original script, adding only a few features to simplify running the test and displaying the results.
Change the config.toml according to your setup.
pip install -r requirements.txt
python run_openai.pyYou can also override settings in configuration file with command line flags like --model, ----category, etc. For example, if you specify --model phi3, all the settings from configuration file will be loaded except model. See python run_openai.py -h for more info.
- If an answer cannot be extracted from the model's response, the script will randomly assign an answer. It's the same way as the original script.
- The total score represents the number of correct answers out of the total number of attempts. This is the score from the original script.
- "Random Guess Attempts" indicates the total number of random guesses out of the total attempts.
- "Correct Random Guesses" shows the number of random guesses that were correct out of all the random guesses.
- "Adjusted Score Without Random Guesses" subtracts all random guesses from the correct answers and the total answers.
- The combined total score in the last column of the table is calculated as: the total number of correct answers across all categories / the total number of all attempts across all categories * 100.
- All the scores in percentage are rounded numbers.