To train models to better understand logical reasoning and Python syntax.
As a set of clean, verified coding challenges for practice. How to Access It
If you are building a custom AI, you run it against these 164 problems to see its "Pass@k" score (the probability that at least one of the generated code samples passes the unit tests). Download 164K txt
The OpenAI HumanEval repository on Hugging Face allows you to download the data in JSONL or TXT-ready formats.
Many developers host mirrors of the HumanEval dataset for easy integration into testing pipelines. Technical Structure To train models to better understand logical reasoning
This dataset is a benchmark created by OpenAI to test "code generation" capabilities. It consists of 164 Python programming tasks that include:
You can find the official version through major AI research repositories: The OpenAI HumanEval repository on Hugging Face allows
The name and parameters of the code to be written. Docstrings: A text description of what the code should do.