Datasets:

TempestTeam
/

dataset-the-stack-v2-dedup-sub

dataset_info:
  config_name: C
  features:
    - name: blob_id
      dtype: string
    - name: directory_id
      dtype: string
    - name: path
      dtype: string
    - name: content_id
      dtype: string
    - name: detected_licenses
      sequence: string
    - name: license_type
      dtype: string
    - name: repo_name
      dtype: string
    - name: snapshot_id
      dtype: string
    - name: revision_id
      dtype: string
    - name: branch_name
      dtype: string
    - name: visit_date
      dtype: timestamp[ns]
    - name: revision_date
      dtype: timestamp[ns]
    - name: committer_date
      dtype: timestamp[ns]
    - name: github_id
      dtype: int64
    - name: star_events_count
      dtype: int64
    - name: fork_events_count
      dtype: int64
    - name: gha_license_id
      dtype: string
    - name: gha_event_created_at
      dtype: timestamp[ns]
    - name: gha_created_at
      dtype: timestamp[ns]
    - name: gha_language
      dtype: string
    - name: src_encoding
      dtype: string
    - name: language
      dtype: string
    - name: is_vendor
      dtype: bool
    - name: is_generated
      dtype: bool
    - name: length_bytes
      dtype: int64
    - name: extension
      dtype: string
    - name: filename
      dtype: string
    - name: content
      dtype: string
  splits:
    - name: train
      num_bytes: 64658205790
      num_examples: 6022485
  download_size: 20685881003
  dataset_size: 64658205790
configs:
  - config_name: C
    data_files:
      - split: train
        path: C/train-*
license: other
task_categories:
  - text-generation
tags:
  - Python
  - Java
  - JavaScript
  - C/C++
size_categories:
  - 10M<n<100M

The Stack v2 Subset with File Contents (Python, Java, JavaScript, C, C++)

TempestTeam/dataset-the-stack-v2-dedup-sub

Dataset Summary

This dataset is a language-filtered and self-contained subset of bigcode/the-stack-v2-dedup, part of the BigCode Project.

It contains only files written in the following programming languages:

Python 🐍
Java ☕
JavaScript 📜
C ⚙️
C++ ⚙️

Unlike the original dataset, which only includes metadata and Software Heritage IDs, this subset includes the actual file contents, enabling out-of-the-box training and analysis of code models, without requiring SWH downloads or AWS credentials.

Use Cases

This dataset is intended for:

Pretraining or fine-tuning Code LLMs on high-quality and permissively licensed code
Language-specific evaluation or benchmarking
Research on code representation, generation, or completion across the 5 selected languages

How to Use

from datasets import load_dataset

ds = load_dataset(
    "TempestTeam/dataset-the-stack-v2-dedup-sub",
    name="Python",
    split="train",
    streaming=True
)

Dataset Structure

Each example in the dataset contains the following fields (inherited from the original Stack v2):

content (string): The full file content, decoded in UTF-8
language (string): Programming language of the file (detected by go-enry / linguist)
path (string): File path within the repository
repo_name (string): Repository name on GitHub
detected_licenses (list of strings): SPDX license identifiers
license_type (string): License type: permissive or no_license
is_vendor (bool): Whether the file is from a dependency
is_generated (bool): Whether the file is detected as generated
length_bytes (int): File size in bytes
Plus other metadata like:
- blob_id, directory_id, revision_id, snapshot_id, visit_date, committer_date
- GitHub metadata: github_id, gha_language, gha_license_id, etc.

Source Dataset

This dataset is derived from:

👉 bigcode/the-stack-v2-dedup

The full Stack v2 dataset is built from the Software Heritage archive and GitHub Archive metadata, and spans 600+ programming languages. This subset narrows the focus to 5 popular languages while retaining full file content.

Curation Rationale

The five selected languages are among the most widely used in open-source projects and code LLM research. By focusing on this curated set, we reduce dataset size, eliminate irrelevant files, and speed up experimentation while preserving linguistic diversity and utility for real-world applications.

License and Legal Considerations

Only permissively licensed files (or those with no license) are included.
Licensing information is provided at file level.
The dataset may contain personal information (e.g., emails, keys) present in public repositories. Sensitive data has been reduced via deduplication but may still exist.
Usage must comply with the original license of each file.

To request the removal of your code, refer to the BigCode opt-out process.

Citation

If you use this dataset, please cite the original Stack v2 paper:

@misc{lozhkov2024starcoder,
  title={StarCoder 2 and The Stack v2: The Next Generation},
  author={Anton Lozhkov and Raymond Li and Loubna Ben Allal and others},
  year={2024},
  eprint={2402.19173},
  archivePrefix={arXiv},
  primaryClass={cs.SE}
}