metadata
license: apache-2.0
pretty_name: HumanEvalPack
language:
- code
Dataset Card for HumanEvalPack
Table of Contents
Dataset Description
- Repository: https://github.com/bigcode-project/octopack
- Paper: WIP
- Point of Contact: Niklas Muennighoff
Dataset Summary
HumanEvalPack is ...
- Languages: Python, JavaScript, Java, Go, C++, Rust
- OctoPack🐙🎒:
Data | CommitPack | 4TB of GitHub commits across 350 programming languages |
---|---|---|
Data | CommitPackFT | Filtered version of CommitPack for high-quality commit messages that resemble instructions |
Model | OctoCoder | StarCoder (16B parameters) instruction tuned on CommitPackFT + OASST |
Evaluation | HumanEvalPack | Extension of OpenAI's HumanEval to cover 3 scenarios across 6 languages |
Dataset Structure
Data Instances
An example looks as follows:
{
"task_id": "Python/0",
"prompt": "from typing import List\n\n\ndef has_close_elements(numbers: List[float], threshold: float) -> bool:\n \"\"\" Check if in given list of numbers, are any two numbers closer to each other than\n given threshold.\n >>> has_close_elements([1.0, 2.0, 3.0], 0.5)\n False\n >>> has_close_elements([1.0, 2.8, 3.0, 4.0, 5.0, 2.0], 0.3)\n True\n \"\"\"\n",
"declaration": "from typing import List\n\n\ndef has_close_elements(numbers: List[float], threshold: float) -> bool:\n",
"canonical_solution": " for idx, elem in enumerate(numbers):\n for idx2, elem2 in enumerate(numbers):\n if idx != idx2:\n distance = abs(elem - elem2)\n if distance < threshold:\n return True\n\n return False\n",
"buggy_solution": " for idx, elem in enumerate(numbers):\n for idx2, elem2 in enumerate(numbers):\n if idx != idx2:\n distance = elem - elem2\n if distance < threshold:\n return True\n\n return False\n",
"bug_type": "missing logic",
"failure_symptoms": "incorrect output",
"entry_point": "has_close_elements",
"import": ""
"test_setup": ""
"test": "\n\n\n\n\ndef check(has_close_elements):\n assert has_close_elements([1.0, 2.0, 3.9, 4.0, 5.0, 2.2], 0.3) == True\n assert has_close_elements([1.0, 2.0, 3.9, 4.0, 5.0, 2.2], 0.05) == False\n assert has_close_elements([1.0, 2.0, 5.9, 4.0, 5.0], 0.95) == True\n assert has_close_elements([1.0, 2.0, 5.9, 4.0, 5.0], 0.8) == False\n assert has_close_elements([1.0, 2.0, 3.0, 4.0, 5.0, 2.0], 0.1) == True\n assert has_close_elements([1.1, 2.2, 3.1, 4.1, 5.1], 1.0) == True\n assert has_close_elements([1.1, 2.2, 3.1, 4.1, 5.1], 0.5) == False\n\ncheck(has_close_elements)",
"example_test": "def check(has_close_elements):\n assert has_close_elements([1.0, 2.0, 3.0], 0.5) == False\n assert has_close_elements([1.0, 2.8, 3.0, 4.0, 5.0, 2.0], 0.3) == True\ncheck(has_close_elements)\n",
"signature": "has_close_elements(numbers: List[float], threshold: float) -> bool",
"docstring": "Check if in given list of numbers, are any two numbers closer to each other than\ngiven threshold.\n>>> has_close_elements([1.0, 2.0, 3.0], 0.5)\nFalse\n>>> has_close_elements([1.0, 2.8, 3.0, 4.0, 5.0, 2.0], 0.3)\nTrue",
"instruction": "Write a Python function `has_close_elements(numbers: List[float], threshold: float) -> bool` to solve the following problem:\nCheck if in given list of numbers, are any two numbers closer to each other than\ngiven threshold.\n>>> has_close_elements([1.0, 2.0, 3.0], 0.5)\nFalse\n>>> has_close_elements([1.0, 2.8, 3.0, 4.0, 5.0, 2.0], 0.3)\nTrue"
}
Data Fields
The data fields are the same among all splits:
task_id
: task id (from 0 to 163)prompt
: the prompt for models relying on code continuationdeclaration
: the declaration of the function (same as prompt but without the docstring)canonical_solution
: the correct solution passing all unit tests for the problembuggy_solution
: same ascanonical_solution
but with a subtle human-written bug causing the unit tests to failbug_type
: the type of the bug inbuggy_solution
(one of [missing logic
,excess logic
,value misuse
,operator misuse
,variable misuse
,function misuse
])failure_symptoms
: the problem the bug causes (one of [incorrect output
,stackoverflow
,infinite loop
])entry_point
: the name of the function- 'import': imports necessary for the solution (only present for Go)
- 'test_setup': imports necessary for the test execution (only present for Go)
test
: the unit tests for the problemexample_test
: additional unit tests different fromtest
that could be e.g. provided to the model (these are not used in the paper)signature
: the signature of the functiondocstring
: the docstring describing the probleminstruction
: an instruction for HumanEvalSynthesize in the formWrite a {language_name} function {signature} to solve the following problem:\n{docstring}
Data Splits
Additional Information
Licensing Information
Each sample has comes from a code repository with a permissive license. The license is provided by the license
field for each sample.
Citation Information