Datasets:
Sub-tasks:
language-modeling
Languages:
py
Multilinguality:
monolingual
Size Categories:
10K<n<100K
Language Creators:
found
Annotations Creators:
no-annotation
Source Datasets:
original
Tags:
License:
| annotations_creators: | |
| - no-annotation | |
| language: | |
| - py | |
| language_creators: | |
| - found | |
| license: | |
| - unknown | |
| multilinguality: | |
| - monolingual | |
| size_categories: | |
| - 10K<n<100K | |
| source_datasets: | |
| - original | |
| task_categories: | |
| - code-generation | |
| - conditional-text-generation | |
| task_ids: | |
| - language-modeling | |
| - code-generation | |
| # Dataset Card for notional-python | |
| ## Table of Contents | |
| - [Dataset Description](#dataset-description) | |
| - [Dataset Summary](#dataset-summary) | |
| - [Languages](#languages) | |
| - [Dataset Creation](#dataset-creation) | |
| - [Curation Rationale](#curation-rationale) | |
| - [Source Data](#source-data) | |
| - [Considerations for Using the Data](#considerations-for-using-the-data) | |
| - [Social Impact of Dataset](#social-impact-of-dataset) | |
| - [Discussion of Biases](#discussion-of-biases) | |
| - [Other Known Limitations](#other-known-limitations) | |
| - [Additional Information](#additional-information) | |
| - [Dataset Curators](#dataset-curators) | |
| - [Licensing Information](#licensing-information) | |
| - [Citation Information](#citation-information) | |
| ## Dataset Description | |
| - **Homepage:** https://notional.ai/ | |
| - **Repository:** [Needs More Information] | |
| - **Paper:** [Needs More Information] | |
| - **Leaderboard:** [Needs More Information] | |
| - **Point of Contact:** [Needs More Information] | |
| ### Dataset Summary | |
| The Notional-python dataset contains python code files from 100 well-known repositories gathered from Google Bigquery Github Dataset. The dataset was created to test the ability of programming language models. | |
| Follow [our repo]() to do the model evaluation using notional-python dataset. | |
| ### Languages | |
| Python | |
| ## Dataset Creation | |
| ### Curation Rationale | |
| Notional-python was built to provide a dataset for testing the ability of the machine to generate python code. | |
| ### Source Data | |
| #### Initial Data Collection and Normalization | |
| The data was obtained by filtering code from [Google Bigquery Github data](https://cloud.google.com/blog/topics/public-datasets/github-on-bigquery-analyze-all-the-open-source-code) | |
| In order to improve the quality of the dataset, only python code files that meet the below conditions are added to the dataset: | |
| - Code with more than 60% of executable lines | |
| - Code with logic, not config files or comment-only files | |
| - Code with more than 30% of attribute declaration lines (E.G.: Some files contain just only class names and their class attributes, usually used for configuration of the project, these files were not selected) | |
| - Code without `TODO` and `FIXME`. | |
| #### Who are the source language producers? | |
| The producers are users of github. | |