|
--- |
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annotations_creators: |
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- no-annotation |
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languages: |
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- py |
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language_creators: |
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- found |
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licenses: |
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- unknown |
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multilinguality: |
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- monolingual |
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size_categories: |
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- 10K<n<100K |
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source_datasets: |
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- original |
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task_categories: |
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- code-generation |
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- conditional-text-generation |
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task_ids: |
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- language-modeling |
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- code-generation |
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--- |
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# Dataset Card for notional-python |
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## Table of Contents |
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- [Dataset Description](#dataset-description) |
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- [Dataset Summary](#dataset-summary) |
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- [Supported Tasks](#supported-tasks-and-leaderboards) |
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- [Languages](#languages) |
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- [Dataset Structure](#dataset-structure) |
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- [Data Instances](#data-instances) |
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- [Data Fields](#data-instances) |
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- [Data Splits](#data-instances) |
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- [Dataset Creation](#dataset-creation) |
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- [Curation Rationale](#curation-rationale) |
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- [Source Data](#source-data) |
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- [Annotations](#annotations) |
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- [Personal and Sensitive Information](#personal-and-sensitive-information) |
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- [Considerations for Using the Data](#considerations-for-using-the-data) |
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- [Social Impact of Dataset](#social-impact-of-dataset) |
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- [Discussion of Biases](#discussion-of-biases) |
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- [Other Known Limitations](#other-known-limitations) |
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- [Additional Information](#additional-information) |
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- [Dataset Curators](#dataset-curators) |
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- [Licensing Information](#licensing-information) |
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- [Citation Information](#citation-information) |
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## Dataset Description |
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- **Homepage:** https://notional.ai/ |
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- **Repository:** [Needs More Information] |
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- **Paper:** [Needs More Information] |
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- **Leaderboard:** [Needs More Information] |
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- **Point of Contact:** [Needs More Information] |
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### Dataset Summary |
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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. |
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Follow [our repo]() to do the model evaluation using notional-python dataset. |
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### Supported Tasks and Leaderboards |
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[Needs More Information] |
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### Languages |
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Python |
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## Dataset Structure |
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### Data Instances |
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[Needs More Information] |
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### Data Fields |
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[Needs More Information] |
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### Data Splits |
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[Needs More Information] |
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## Dataset Creation |
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### Curation Rationale |
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Notional-python was built to provide a dataset for testing the ability of the machine to generate python code. |
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### Source Data |
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#### Initial Data Collection and Normalization |
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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) |
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In order to improve the quality of the dataset, only python code files that meet the below conditions are added to the dataset: |
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- Code with more than 60% of executable lines |
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- Code with logic, not config files or comment-only files |
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- 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) |
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- Code without `TODO` and `FIXME`. |
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#### Who are the source language producers? |
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The producers are users of github. |
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### Annotations |
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#### Annotation process |
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[Needs More Information] |
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#### Who are the annotators? |
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[Needs More Information] |
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### Personal and Sensitive Information |
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[Needs More Information] |
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## Considerations for Using the Data |
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### Social Impact of Dataset |
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[Needs More Information] |
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### Discussion of Biases |
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[Needs More Information] |
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### Other Known Limitations |
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[Needs More Information] |
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## Additional Information |
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### Dataset Curators |
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[Needs More Information] |
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### Licensing Information |
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[Needs More Information] |
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### Citation Information |
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[Needs More Information] |
