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metadata
dataset_info:
  features:
    - name: url
      dtype: string
    - name: repository_url
      dtype: string
    - name: labels_url
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    - name: comments_url
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        - name: type
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        - name: url
          dtype: string
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    - name: labels
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        - name: archived_at
          dtype: 'null'
        - name: archived_by
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        - name: color
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        - name: login
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        - name: organizations_url
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        - name: repos_url
          dtype: string
        - name: site_admin
          dtype: bool
        - name: starred_url
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          dtype: string
        - name: type
          dtype: string
        - name: url
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          dtype: string
    - name: milestone
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        - name: closed_at
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        - name: closed_issues
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    - name: issue_dependencies_summary
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        - name: total_blocking
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    - name: pinned_comment
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    - name: label_names
      sequence: string
  splits:
    - name: train
      num_bytes: 19220900
      num_examples: 4900
  download_size: 4613131
  dataset_size: 19220900
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
license: other
task_categories:
  - text-classification
  - text-retrieval
language:
  - en
tags:
  - github-issues
  - practice
pretty_name: GitHub Issues from huggingface/datasets
size_categories:
  - 1K<n<10K

GitHub Issues – huggingface/datasets (raw)

Dataset Summary

A corpus of GitHub issues and pull requests from the JPEG XL support repository. Created as a practice exercise following AT1-Task01 and Hugging Face LLM Course ("Creating your own dataset").

How the data was collected

  • Source: GitHub REST API (/repos/huggingface/datasets/issues, state=all)
  • Collected on: 2026-10-05
  • Pull requests are included; they can be identified by the pull_request field (it is None for regular issues).
  • This "raw" version keeps the original API fields with minimal processing and does not include issue comments.

Data Collection Process

  1. Authentication: A read-only GitHub personal access token was stored in Kaggle Secret Key , and loaded at runtime. It was never written into the notebook.
  2. Collection: Issues and pull requests were requested from the GitHub REST API using Python requests, page by page, staying within GitHub's rate limit of 5,000 requests per hour.
  3. Raw storage: Responses were saved as a JSON Lines file.
  4. Loading: The file was loaded with `datasets.load_dataset.
  5. Cleaning: 100 duplicate records (caused by a pagination error) were removed using number as a unique key.
  6. Augmentation: Derived fields were added.
  7. Publishing: The dataset was pushed to the Hugging Face Hub with push_to_hub(), authenticated with a Hugging Face write token stored in Secret Keys.

Dataset Structure

Each row is one issue or pull request. Key fields:

  • number – issue/PR number
  • title – title
  • body – description text
  • labels – GitHub labels
  • state – open or closed
  • created_at, closed_at – timestamps
  • pull_request – present only for pull requests

Intended Uses

  • Learning to build and share datasets with 🤗 Hugging Face Datasets
  • Exploring how long issues take to close
  • Multilabel classification of issue labels
  • Semantic search over issues

Storage, Locations and Versioning

| Item | Location | Versioning | | Published dataset | https://huggingface.co/datasets/Color0106/github-raw | Hugging Face commit history (Files and versions → History) | | Raw data | Collection date: [2026-10-05] | | Notebook 1 – Collection & augmentation | [Kaggle Notebook] | [Ver 1 / 2026-10-05] | | Notebook 2 – Transformers pipeline | [Colab Notebook] | [Ver 2 / 2026/10/18] | | Notebook 3 – Semantic search (FAISS) | [Colab Notebook] | [Ver 1 / 2026/10/18] | | Access tokens | Kaggle Secrets / Colab Secrets — not stored in any file | Expire on [2026/12/05] |

Limitations

  • A snapshot in time; newer issues are not included.
  • Only a subset of all issues was collected.
  • Text was written by GitHub users and may contain usernames, code, and links.

Legal and Policy Compliance

| Legislation / code / policy | How it applies | How this project complies |

| Privacy Act 1988 (Cth) – Australian Privacy Principles | Usernames, profile links and free text may contain personal information | Data limited to what is needed for the task; personal information is not used to profile individuals;|

| Copyright Act 1968 (Cth) | Issue text is written by GitHub users and is their work | No new licence is claimed; content is attributed and used for education | | GitHub Terms of Service and API terms | Governs use of GitHub content and the API | Official API used, rate limits respected, source attributed |

| Hugging Face Content Policy | Governs what can be published on the Hub | Dataset contains public, non-sensitive technical discussion |

| North Metropolitan TAFE data storage and management policy |

License

Issue content belongs to the original GitHub authors and is subject to GitHub's Terms of Service.

Shared here for educational purposes.

References