| --- |
| annotations_creators: |
| - machine-generated |
| language: |
| - en |
| language_creators: |
| - machine-generated |
| - expert-generated |
| license: |
| - mit |
| multilinguality: |
| - monolingual |
| pretty_name: MultiPLE-E |
| size_categories: |
| - 1K<n<10K |
| source_datasets: |
| - original |
| - extended|openai_humaneval |
| tags: [] |
| task_categories: [] |
| task_ids: [] |
| --- |
| |
| # Dataset Card for MultiPL-E |
|
|
| ## Dataset Description |
|
|
| - **Homepage:** https://nuprl.github.io/MultiPL-E/ |
| - **Repository:** https://github.com/nuprl/MultiPL-E |
| - **Paper:** https://arxiv.org/abs/2208.08227 |
| - **Point of Contact:** carolyn.anderson@wellesley.edu, mfeldman@oberlin.edu, a.guha@northeastern.edu |
|
|
| ## Dataset Summary |
|
|
| MultiPL-E is a dataset for evaluating large language models for code |
| generation that supports 18 programming languages. It takes the OpenAI |
| "HumanEval" Python benchmarks and uses little compilers to translate them |
| to other languages. It is easy to add support for new languages and benchmarks. |
|
|
| [More Information Needed] |
|
|
|
|
