| | --- |
| | annotations_creators: |
| | - no-annotation |
| | language_creators: |
| | - found |
| | language: |
| | - py |
| | license: |
| | - unknown |
| | multilinguality: |
| | - monolingual |
| | size_categories: |
| | - 10K<n<100K |
| | source_datasets: |
| | - original |
| | task_categories: |
| | - text2text-generation |
| | task_ids: |
| | - language-modeling |
| | tags: |
| | - conditional-text-generation |
| | - 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. |
| |
|
