| --- |
| annotations_creators: |
| - expert-generated |
| language_creators: |
| - expert-generated |
| language: |
| - code |
| license: |
| - mit |
| multilinguality: |
| - monolingual |
| source_datasets: |
| - original |
| task_categories: |
| - text2text-generation |
| task_ids: [] |
| pretty_name: OpenAI HumanEval-Infilling |
| tags: |
| - code-generation |
| --- |
| |
| # HumanEval-Infilling |
|
|
|
|
| ## Dataset Description |
|
|
| - **Repository:** https://github.com/openai/human-eval-infilling |
| - **Paper:** https://arxiv.org/pdf/2207.14255 |
|
|
| ## Dataset Summary |
|
|
| [HumanEval-Infilling](https://github.com/openai/human-eval-infilling) is a benchmark for infilling tasks, derived from [HumanEval](https://huggingface.co/datasets/openai_humaneval) benchmark for the evaluation of code generation models. |
|
|
| ## Dataset Structure |
| To load the dataset you need to specify a subset. By default `HumanEval-SingleLineInfilling` is loaded. |
|
|
| ```python |
| from datasets import load_dataset |
| ds = load_dataset("humaneval_infilling", "HumanEval-RandomSpanInfilling") |
| |
| DatasetDict({ |
| test: Dataset({ |
| features: ['task_id', 'entry_point', 'prompt', 'suffix', 'canonical_solution', 'test'], |
| num_rows: 1640 |
| }) |
| }) |
| ``` |
|
|
| ## Subsets |
|
|
| This dataset has 4 subsets: HumanEval-MultiLineInfilling, HumanEval-SingleLineInfilling, HumanEval-RandomSpanInfilling, HumanEval-RandomSpanInfillingLight. |
| The single-line, multi-line, random span infilling and its light version have 1033, 5815, 1640 and 164 tasks, respectively. |
|
|
| ## Citation |
|
|
| ``` |
| @article{bavarian2022efficient, |
| title={Efficient Training of Language Models to Fill in the Middle}, |
| author={Bavarian, Mohammad and Jun, Heewoo and Tezak, Nikolas and Schulman, John and McLeavey, Christine and Tworek, Jerry and Chen, Mark}, |
| journal={arXiv preprint arXiv:2207.14255}, |
| year={2022} |
| } |
| ``` |
