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---
dataset_info:
  features:
  - name: url
    dtype: large_string
  - name: repository_url
    dtype: large_string
  - name: labels_url
    dtype: large_string
  - name: comments_url
    dtype: large_string
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    - name: organizations_url
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    - name: repos_url
      dtype: string
    - name: events_url
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    - name: received_events_url
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    - name: type
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    - name: user_view_type
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    - name: site_admin
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    - name: node_id
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    - name: url
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    - name: color
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    - name: default
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    - name: description
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  - name: locked
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      dtype: string
    - name: id
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    - name: node_id
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    - name: gravatar_id
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      dtype: string
    - name: following_url
      dtype: string
    - name: gists_url
      dtype: string
    - name: starred_url
      dtype: string
    - name: subscriptions_url
      dtype: string
    - name: organizations_url
      dtype: string
    - name: repos_url
      dtype: string
    - name: events_url
      dtype: string
    - name: received_events_url
      dtype: string
    - name: type
      dtype: string
    - name: user_view_type
      dtype: string
    - name: site_admin
      dtype: bool
  - name: milestone
    dtype: float64
  - name: comments
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    dtype: timestamp[us, tz=UTC]
  - name: updated_at
    dtype: timestamp[us, tz=UTC]
  - name: closed_at
    dtype: timestamp[us, tz=UTC]
  - name: assignee
    struct:
    - name: login
      dtype: string
    - name: id
      dtype: float64
    - name: node_id
      dtype: string
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    - name: gravatar_id
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    - name: html_url
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    - name: following_url
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    - name: gists_url
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    - name: starred_url
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    list: 'null'
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    - name: diff_url
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    - name: patch_url
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    - name: merged_at
      dtype: string
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  - name: closed_by
    struct:
    - name: login
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    - name: id
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    - name: node_id
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    - name: avatar_url
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    - name: gravatar_id
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    - name: url
      dtype: string
    - name: html_url
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    - name: followers_url
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    - name: following_url
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    - name: gists_url
      dtype: string
    - name: starred_url
      dtype: string
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    - name: organizations_url
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    - name: repos_url
      dtype: string
    - name: events_url
      dtype: string
    - name: received_events_url
      dtype: string
    - name: type
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    - name: user_view_type
      dtype: string
    - name: site_admin
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  - name: reactions
    struct:
    - name: url
      dtype: string
    - name: total_count
      dtype: int64
    - name: '+1'
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    - name: '-1'
      dtype: int64
    - name: laugh
      dtype: int64
    - name: hooray
      dtype: int64
    - name: confused
      dtype: int64
    - name: heart
      dtype: int64
    - name: rocket
      dtype: int64
    - name: eyes
      dtype: int64
  - name: timeline_url
    dtype: large_string
  - name: performed_via_github_app
    dtype: float64
  - name: state_reason
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  - name: sub_issues_summary
    struct:
    - name: total
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    - name: completed
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    - name: percent_completed
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  - name: issue_dependencies_summary
    struct:
    - name: blocked_by
      dtype: float64
    - name: total_blocked_by
      dtype: float64
    - name: blocking
      dtype: float64
    - name: total_blocking
      dtype: float64
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    dtype: bool
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    list: string
  splits:
  - name: train
    num_bytes: 267859196
    num_examples: 41618
  download_size: 185645233
  dataset_size: 267859196
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
license: apache-2.0
task_categories:
- text-classification
- summarization
language:
- en
tags:
- github
- issues
- bug-report
- pull-request
- software-engineering
- transformers
- huggingface
pretty_name: HuggingFace Transformers GitHub Issues
size_categories:
- 10K<n<100K
---

# HuggingFace Transformers GitHub Issues Dataset

## Dataset Description

This dataset contains **all issues and pull requests** (open and closed) from the [`huggingface/transformers`](https://github.com/huggingface/transformers) GitHub repository, along with their comment threads. It was collected on **July 19-20, 2026** via the [GitHub REST API](https://docs.github.com/en/rest/issues/issues) and follows the workflow described in the [Hugging Face NLP course — Creating your own dataset](https://huggingface.co/learn/nlp-course/chapter5/6).

- **Repository:** [huggingface/transformers](https://github.com/huggingface/transformers)
- **Total rows:** 41,618 (issues + pull requests)
- **Date range:** November 3, 2018 → July 19, 2026
- **Format:** Parquet (single shard, `train` split)

## Dataset Structure

### Splits

| Split | Num examples |
|-------|-------------:|
| train | 41,618       |

### Composition

| Type            | Count  |
|-----------------|-------:|
| Issues          | 17,960 |
| Pull requests   | 23,658 |
| Open            |  1,900 |
| Closed          | 39,718 |
| With labels     |  9,665 |
| With comments   | 37,174 |
| Total comments  | 159,388 |

### Key Columns

| Column              | Type      | Description                                                                 |
|---------------------|-----------|-----------------------------------------------------------------------------|
| `number`            | int64     | GitHub issue/PR number (unique, no duplicates)                              |
| `title`             | string    | Issue/PR title                                                              |
| `body`              | string    | Issue/PR body (Markdown; 251 nulls + 688 empty — normal)                    |
| `state`             | string    | `open` or `closed`                                                          |
| `is_pull_request`   | bool      | `True` if this row is a PR, `False` if it's an issue                        |
| `labels`            | list      | List of label objects (`name`, `color`, `id`, ...) — 9,665 rows have labels |
| `comments`          | int64     | Number of comments on the issue                                             |
| `comments_text`     | list[str] | The body text of each comment (fetched separately via the comments API)     |
| `user`              | struct    | The author (login, id, avatar_url, type, ...)                               |
| `created_at`        | timestamp | When the issue/PR was created                                               |
| `updated_at`        | timestamp | When it was last updated                                                    |
| `closed_at`         | timestamp | When it was closed (null for 1,900 open issues)                             |
| `reactions`         | struct    | Reaction counts (+1, -1, laugh, heart, rocket, eyes, ...)                   |
| `pull_request`      | struct    | PR metadata (url, diff_url, patch_url, merged_at) — null for issues         |
| `assignees`         | list      | Assigned users                                                              |
| `milestone`         | float64   | Milestone (100% null for this repo)                                         |

### Top Labels

| Label              | Count |
|--------------------|------:|
| wontfix            | 2,633 |
| bug                | 2,495 |
| Feature request    |   786 |
| New model          |   683 |
| model card         |   654 |
| WIP                |   380 |
| Vision             |   268 |
| run-slow           |   198 |
| Code agent slop    |   189 |
| dependencies       |   188 |
| Good First Issue   |   183 |
| Core: Tokenization |   170 |
| Audio              |   166 |
| trainer            |   146 |
| Good Second Issue  |   129 |

## Collection Methodology

The dataset was collected using a custom Python script ([`prepare_dataset.py`](https://github.com/)) that:

1. **Fetched all issues + PRs** using the GitHub REST API with `since`-based pagination (sorted by `updated_at` ascending) to bypass GitHub's 10,000-record page-number cap. Issues were written incrementally to a JSONL file for crash recovery.
2. **Added an `is_pull_request` flag** based on whether the `pull_request` field is present.
3. **Pushed the issues-only dataset to the Hub** (as a safety checkpoint before the long comment fetch).
4. **Fetched comment bodies** for every issue with `comments > 0` (4,441 zero-comment issues were skipped as an optimization). Comments were fetched with `per_page=100` to minimize pagination requests.
5. **Pushed the final dataset** (issues + comments) to the Hub.

GitHub's authenticated rate limit (5,000 requests/hour) was respected throughout — the script sleeps until the rate-limit window resets when the budget is exhausted, with a one-hour fallback sleep if the reset header is missing.

## Known Limitations

- **5,799 missing issue numbers** in the range 1–47,417: these correspond to deleted issues/PRs on GitHub that cannot be retrieved via the API. This is expected and unavoidable.
- **65 minor mismatches** between the `comments` count field and the length of `comments_text`: these occur when comments were added or deleted between the issue fetch and the comment fetch. The `comments` field reflects the count at fetch time; `comments_text` reflects the actual comments retrieved.
- **`milestone`, `performed_via_github_app`, `pinned_comment`** are 100% null — these fields are not used on this repository.
- **`body` has 251 nulls and 688 empty strings** — some issues/PRs simply have no body text.
- The dataset includes **both issues and pull requests** (GitHub's issues endpoint returns both). Use the `is_pull_request` column to filter.

## Potential Use Cases

- **Issue classification:** Train a model to categorize issues (bug, feature request, question) based on title + body.
- **Bug triage:** Predict which label an issue should have, or whether it's likely to be closed.
- **Duplicate detection:** Find semantically similar issues using embeddings of title + body.
- **Pull request summarization:** Summarize long PR bodies or comment threads.
- **Software engineering research:** Analyze issue lifecycle, response times, contributor activity, label distributions, etc.
- **LLM fine-tuning:** Build instruction-tuning datasets for "classify this issue" or "summarize this thread" tasks.

## Licensing

The dataset is derived from public GitHub issue data from the [`huggingface/transformers`](https://github.com/huggingface/transformers) repository, which is licensed under [Apache 2.0](https://github.com/huggingface/transformers/blob/main/LICENSE). The dataset is provided under the same license.

## Citation

If you use this dataset, please cite:

```bibtex
@misc{transformers-issues-dataset,
  author       = {Noamaan Mulla},
  title        = {HuggingFace Transformers GitHub Issues Dataset},
  year         = {2026},
  url          = {https://huggingface.co/datasets/noamaanMulla-03/transformers-issues},
  note         = {Collected via the GitHub REST API on July 19-20, 2026}
}
```

Also cite the original repository:

```bibtex
@misc{wolf2019huggingface,
  author       = {Thomas Wolf and Lysandre Debut and Victor Sanh and Julien Chaumond and Clement Delangue and Anthony Moi and Pierric Cistac and Tim Rault and Rémi Louf and Morgan Funtowicz and Joe Davison and Sam Shleifer and Patrick von Platen and Clara Ma and Yacine Jernite and Julien Plu and Canwen Xu and Teven Le Scao and Sylvain Gugger and Mariama Drame and Quentin Lhoest and Alexander M. Rush},
  title        = {HuggingFace's Transformers: State-of-the-art Natural Language Processing},
  year         = {2019},
  publisher    = {GitHub},
  howpublished = {\url{https://github.com/huggingface/transformers}}
}
```