--- license: mit pretty_name: HumanEvalPack language_creators: - expert-generated multilinguality: - multilingual language: - code tags: - code dataset_info: - config_name: cpp features: - name: task_id dtype: string - name: prompt dtype: string - name: declaration dtype: string - name: canonical_solution dtype: string - name: buggy_solution dtype: string - name: bug_type dtype: string - name: failure_symptoms dtype: string - name: entry_point dtype: string - name: import dtype: string - name: test_setup dtype: string - name: test dtype: string - name: example_test dtype: string - name: signature dtype: string - name: docstring dtype: string - name: instruction dtype: string splits: - name: test num_bytes: 469111 num_examples: 164 download_size: 193981 dataset_size: 469111 - config_name: go features: - name: task_id dtype: string - name: prompt dtype: string - name: declaration dtype: string - name: canonical_solution dtype: string - name: buggy_solution dtype: string - name: bug_type dtype: string - name: failure_symptoms dtype: string - name: entry_point dtype: string - name: import dtype: string - name: test_setup dtype: string - name: test dtype: string - name: example_test dtype: string - name: signature dtype: string - name: docstring dtype: string - name: instruction dtype: string splits: - name: test num_bytes: 463234 num_examples: 164 download_size: 198394 dataset_size: 463234 - config_name: java features: - name: task_id dtype: string - name: prompt dtype: string - name: declaration dtype: string - name: canonical_solution dtype: string - name: buggy_solution dtype: string - name: bug_type dtype: string - name: failure_symptoms dtype: string - name: entry_point dtype: string - name: import dtype: string - name: test_setup dtype: string - name: test dtype: string - name: example_test dtype: string - name: signature dtype: string - name: docstring dtype: string - name: instruction dtype: string splits: - name: test num_bytes: 589440 num_examples: 164 download_size: 210440 dataset_size: 589440 - config_name: js features: - name: task_id dtype: string - name: prompt dtype: string - name: declaration dtype: string - name: canonical_solution dtype: string - name: buggy_solution dtype: string - name: bug_type dtype: string - name: failure_symptoms dtype: string - name: entry_point dtype: string - name: import dtype: string - name: test_setup dtype: string - name: test dtype: string - name: example_test dtype: string - name: signature dtype: string - name: docstring dtype: string - name: instruction dtype: string splits: - name: test num_bytes: 435189 num_examples: 164 download_size: 194044 dataset_size: 435189 - config_name: python features: - name: task_id dtype: string - name: prompt dtype: string - name: declaration dtype: string - name: canonical_solution dtype: string - name: buggy_solution dtype: string - name: bug_type dtype: string - name: failure_symptoms dtype: string - name: entry_point dtype: string - name: import dtype: string - name: test_setup dtype: string - name: test dtype: string - name: example_test dtype: string - name: signature dtype: string - name: docstring dtype: string - name: instruction dtype: string splits: - name: test num_bytes: 423013 num_examples: 164 download_size: 191279 dataset_size: 423013 - config_name: rust features: - name: task_id dtype: string - name: prompt dtype: string - name: declaration dtype: string - name: canonical_solution dtype: string - name: buggy_solution dtype: string - name: bug_type dtype: string - name: failure_symptoms dtype: string - name: entry_point dtype: string - name: import dtype: string - name: test_setup dtype: string - name: test dtype: string - name: example_test dtype: string - name: signature dtype: string - name: docstring dtype: string - name: instruction dtype: string splits: - name: test num_bytes: 450539 num_examples: 164 download_size: 168464 dataset_size: 450539 configs: - config_name: cpp data_files: - split: test path: cpp/test-* - config_name: go data_files: - split: test path: go/test-* - config_name: java data_files: - split: test path: java/test-* - config_name: js data_files: - split: test path: js/test-* - config_name: python data_files: - split: test path: python/test-* default: true - config_name: rust data_files: - split: test path: rust/test-* --- ![Octopack](https://github.com/bigcode-project/octopack/blob/31f3320f098703c7910e43492c39366eeea68d83/banner.png?raw=true) # Dataset Card for HumanEvalPack ## Table of Contents - [Table of Contents](#table-of-contents) - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Additional Information](#additional-information) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - **Repository:** https://github.com/bigcode-project/octopack - **Paper:** [OctoPack: Instruction Tuning Code Large Language Models](https://arxiv.org/abs/2308.07124) - **Point of Contact:** [Niklas Muennighoff](mailto:n.muennighoff@gmail.com) ### Dataset Summary > HumanEvalPack is an extension of OpenAI's HumanEval to cover 6 total languages across 3 tasks. The Python split is exactly the same as OpenAI's Python HumanEval. The other splits are translated by humans (similar to HumanEval-X but with additional cleaning, see [here](https://github.com/bigcode-project/octopack/tree/main/evaluation/create/humaneval-x#modifications-muennighoff)). Refer to the [OctoPack paper](https://arxiv.org/abs/2308.07124) for more details. > - **Languages:** Python, JavaScript, Java, Go, C++, Rust - **OctoPack🐙🎒:**
Data CommitPack 4TB of GitHub commits across 350 programming languages
CommitPackFT Filtered version of CommitPack for high-quality commit messages that resemble instructions
Model OctoCoder StarCoder (16B parameters) instruction tuned on CommitPackFT + OASST
OctoGeeX CodeGeeX2 (6B parameters) instruction tuned on CommitPackFT + OASST
Evaluation HumanEvalPack Extension of OpenAI's HumanEval to cover 3 scenarios across 6 languages
## Usage ```python # pip install -q datasets from datasets import load_dataset # Languages: "python", "js", "java", "go", "cpp", "rust" ds = load_dataset("bigcode/humanevalpack", "python")["test"] ds[0] ``` ## Dataset Structure ### Data Instances An example looks as follows: ```json { "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`: Indicates the language (Python/JavaScript/Java/Go/C++/Rust) and task id (from 0 to 163) of the problem - `prompt`: the prompt for models relying on code continuation - `declaration`: the declaration of the function (same as prompt but without the docstring) - `canonical_solution`: the correct solution passing all unit tests for the problem - `buggy_solution`: same as `canonical_solution` but with a subtle human-written bug causing the unit tests to fail - `bug_type`: the type of the bug in `buggy_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 problem - `example_test`: additional unit tests different from `test` that could be e.g. provided to the model (these are not used in the paper) - `signature`: the signature of the function - `docstring`: the docstring describing the problem - `instruction`: an instruction for HumanEvalSynthesize in the form `Write a {language_name} function {signature} to solve the following problem:\n{docstring}` ## Citation Information ```bibtex @article{muennighoff2023octopack, title={OctoPack: Instruction Tuning Code Large Language Models}, author={Niklas Muennighoff and Qian Liu and Armel Zebaze and Qinkai Zheng and Binyuan Hui and Terry Yue Zhuo and Swayam Singh and Xiangru Tang and Leandro von Werra and Shayne Longpre}, journal={arXiv preprint arXiv:2308.07124}, year={2023} } ```