---
annotations_creators:
- no-annotation
language:
- en
language_creators:
- found
license:
- unknown
multilinguality:
- multilingual
pretty_name: Hugging Face Github Issues
size_categories:
- 1K<n<10K
source_datasets:
- original
tags:
- hugging
- spaces
- issues
task_categories:
- text-classification
- text-retrieval
task_ids:
- multi-class-classification
- multi-label-classification
- document-retrieval

dataset_info:
  features:
  - name: id
    dtype: int64
  - name: number
    dtype: int64
  - name: title
    dtype: string
  - name: state
    dtype: string
  - name: created_at
    dtype: timestamp[s]
  - name: updated_at
    dtype: timestamp[s]
  - name: closed_at
    dtype: timestamp[s]
  - name: html_url
    dtype: string
  - name: pull_request
    struct:
    - name: url
      dtype: string
    - name: html_url
      dtype: string
    - name: diff_url
      dtype: string
    - name: patch_url
      dtype: string
    - name: merged_at
      dtype: timestamp[s]
  - name: user_login
    dtype: string
  - name: is_pull_request
    dtype: bool
  - name: comments
    list: string
  splits:
  - name: train
    num_bytes: 18163393
    num_examples: 5000
  download_size: 6138126
  dataset_size: 18163393
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
---


# Hugging Face Github Issues

This dataset contains **5000 GitHub issues** collected from Hugging Face repositories.  
It includes issue metadata, content, labels, user information, timestamps, and comments.  
The dataset is suitable for text classification, multi-label classification, and document retrieval tasks.

## Dataset Structure

### Columns

- `id` — Internal ID of the issue (int64)  
- `number` — GitHub issue number (int64)  
- `title` — Title of the issue (string)  
- `state` — Issue state: open/closed (string)  
- `created_at` — Timestamp when the issue was created (timestamp[s])  
- `updated_at` — Timestamp when the issue was last updated (timestamp[s])  
- `closed_at` — Timestamp when the issue was closed (timestamp[s])  
- `html_url` — URL to the GitHub issue (string)  
- `pull_request` — Struct containing PR info (if the issue is a PR):  
  - `url` — URL to PR  
  - `html_url` — HTML URL of PR  
  - `diff_url` — Diff URL  
  - `patch_url` — Patch URL  
  - `merged_at` — Merge timestamp (timestamp[s])  
- `user_login` — Login of the issue creator (string)  
- `is_pull_request` — Whether the issue is a pull request (bool)  
- `comments` — List of comments on the issue (list[string])  

### Splits

- `train` — 5000 examples

## Supported Tasks

- **Text Classification:** Predict labels or categories of issues  
- **Multi-label Classification:** Issues may have multiple labels  
- **Document Retrieval:** Retrieve relevant issues based on a query  

## Languages

- English

## Dataset Creation

The dataset was collected using the **GitHub API**, including all issue metadata and comments.

## Usage Example

```python
from datasets import load_dataset

dataset = load_dataset("cicboy/github-issues", split="train")

# Preview first 5 examples
for i, example in enumerate(dataset[:5]):
    print(f"Issue #{example['number']}: {example['title']}")
    print(f"Created at: {example['created_at']}, Closed at: {example['closed_at']}")
    print(f"User: {example['user_login']}, PR: {example['is_pull_request']}")
    print(f"Comments: {example['comments'][:3]}")  # first 3 comments
    print()

## <u>**Citation**</u>

@misc{cicboy_github_issues,
  author = {Cicboy},
  title = {Hugging Face Github Issues Dataset},
  year = {2025},
  howpublished = {\url{https://huggingface.co/datasets/cicboy/github-issues}}
}