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Nemotron-Pretraining-Code-v3

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Nemotron-Pretraining-Code-v3

Dataset Description:

The Nemotron-Pretraining-Code-v3 dataset is part of the Nemotron Pretraining Data collection of pretraining datasets. Designed for the NVIDIA Nemotron 3 family of LLMs, this dataset is intended to improve the coding capabilities of LLMs.

The Nemotron-Pretraining-Code-v3 dataset contains the metadata corresponding to the raw source-code update to our Nemotron-Pretraining-Code-v2 and Nemotron-Pretraining-Code-v1 source-code corpora. It adds 146 M new files (173 B tokens) from GitHub (with a cut-off date of September 30, 2025). This dataset contains only incrementally new files and is meant to be used jointly with the v2 and v1 corpora.

The dataset contains a single split Nemotron-Code-Metadata with the following columns:

  • commit_id: The first seven characters of the Git commit hash
  • rel_path: The file path of the content relative to the repository root directory
  • language: The detected programming language of the content

This dataset is ready for commercial use.

Dataset Owner(s):

NVIDIA Corporation

Dataset Creation Date:

05/18/2026

Version:

Nemotron-Pretraining-Code-v3

Previous Version(s):

Relationship to Previous Version(s): This is an extension of the previously released datasets. They are meant to be used together.

License/Terms of Use:

The Nemotron-Pretraining-Code-v3 dataset is licensed under the Creative Commons Attribution 4.0 International License (CC-BY-4.0).

Intended Usage:

The Nemotron-Pretaining-Code-v3 Dataset is intended to be used by the community to continue to improve open models.

Dataset Characterization

Data Collection Method: Automated

Labeling Method: Automated

Dataset Format

Modality: Text

Format: Parquet

Dataset Quantification

Record Count: 146.3M samples

Measurement of Total Data Storage: 8.2 GB

Reference(s):

If you use our dataset in your research, please cite our NVIDIA Nemotron 3 Ultra tech report.

Ethical Considerations:

NVIDIA believes Trustworthy AI is a shared responsibility and we have established policies and practices to enable development for a wide array of AI applications. Developers should work with their internal developer teams to ensure this dataset meets requirements for the relevant industry and use case and addresses unforeseen product misuse.

Please report quality, risk, security vulnerabilities or NVIDIA AI Concerns here.
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