Datasets:
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README.md
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splits:
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- name: train
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num_bytes:
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num_examples: 4716175
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download_size:
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dataset_size:
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---
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dtype: string
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splits:
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- name: train
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num_bytes: 63445188751
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num_examples: 4716175
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download_size: 21776760509
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dataset_size: 63445188751
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license: bigscience-openrail-m
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task_categories:
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- text-generation
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language:
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- en
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pretty_name: arxiv_research_code
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size_categories:
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- 10B<n<100B
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---
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# Dataset Card for "ArtifactAI/arxiv_research_code"
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## Dataset Description
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https://huggingface.co/datasets/ArtifactAI/arxiv_research_code
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### Dataset Summary
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ArtifactAI/arxiv_research_code contains over 21.8GB of source code files referenced strictly in ArXiv papers. The dataset serves as a curated dataset for Code LLMs.
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### How to use it
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```python
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from datasets import load_dataset
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# full dataset (21.8GB of data)
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ds = load_dataset("ArtifactAI/arxiv_research_code", split="train")
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# dataset streaming (will only download the data as needed)
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ds = load_dataset("ArtifactAI/arxiv_research_code", streaming=True, split="train")
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for sample in iter(ds): print(sample["code"])
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```
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## Dataset Structure
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### Data Instances
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Each data instance corresponds to one file. The content of the file is in the `code` feature, and other features (`repo`, `file`, etc.) provide some metadata.
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### Data Fields
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- `repo` (string): code repository name.
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- `file` (string): file path in the repository.
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- `code` (string): code within the file.
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- `file_length`: (integer): number of characters in the file.
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- `avg_line_length`: (float): the average line-length of the file.
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- `max_line_length`: (integer): the maximum line-length of the file.
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- `extension_type`: (string): file extension.
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### Data Splits
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The dataset has no splits and all data is loaded as train split by default.
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## Dataset Creation
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### Source Data
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#### Initial Data Collection and Normalization
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34,099 active GitHub repository names were extracted from [ArXiv](https://arxiv.org/) papers from its inception through July 21st, 2023 totaling 773G of compressed github repositories.
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These repositories were then filtered, and the code from each file was extracted into 4.7 million files.
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#### Who are the source language producers?
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The source (code) language producers are users of GitHub that created unique repository
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### Personal and Sensitive Information
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The released dataset may contain sensitive information such as emails, IP addresses, and API/ssh keys that have previously been published to public repositories on GitHub.
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## Additional Information
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### Dataset Curators
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Matthew Kenney, Artifact AI, [email protected]
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### Citation Information
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```
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@misc{arxiv_research_code,
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title={arxiv_research_code},
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author={Matthew Kenney},
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year={2023}
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}
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```
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