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README.md

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----
-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.

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