Update README.md

README.md

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 pretty_name: Hugging Face Datasets GitHub Issues
 size_categories:
 - 1K<n<10K
----
+---
+# Dataset Card for Dataset Name
+
+## Dataset Details
+
+### Dataset Description
+
+This dataset is a collection of **GitHub Issue and Pull Request metadata** scraped from the public **`huggingface/datasets`** repository using the GitHub REST API. It contains **3,261 distinct issue records** (excluding pull requests) that were extracted from an initial fetch of 7,808 samples. The data provides a rich corpus of **real-world technical communication** focused on open-source software development, covering the repository's activity up to late 2025.
+
+The data provides a rich corpus of **real-world technical communication**, primarily in **English (en)**, focused on the **open-source software development** domain of the `datasets` library. The dataset was curated to offer a clean, usable source for tasks like **issue classification** and **summarization** within a highly technical context.
+
+## Uses
+
+This simplified dataset primarily supports tasks based on textual content and intrinsic labels (`state`).
+
+**text-classification: Issue State Classification**
+The dataset can be used to train a model for **Issue State Classification**, which consists in **predicting whether an issue/pull request is currently 'open' or 'closed'** based solely on its `title` and `body` text. Success on this task is typically measured by achieving a high **Accuracy** or **F1-score**.
+
+**other:issue-summarization**
+The dataset can be used to train a model for **Issue Summarization** (Sequence-to-Sequence), which consists in **generating a concise title/summary** given the longer `body` text of the issue. Success on this task is typically measured by achieving a high **ROUGE-L** score.
+
+**other:issue-type-classification**
+The dataset can be used to train a model for **Issue Type Classification**, which consists in **classifying whether a record represents a bug, a feature request, or general question** (derived or annotated from the `title` and `body` fields).
+
+### Languages
+
+The primary language represented in the dataset is **English (en)** (BCP-47 code: `en`), consistent with standard practice for global open-source projects. The text is technical, informal, and conversational, reflecting developer communication on a platform like GitHub.
+
+
+## Dataset Structure
+
+{
+  "url": "String",
+  "repository_url": "String",
+  "labels_url": "String",
+  "comments_url": "String",
+  "events_url": "String",
+  "html_url": "String",
+  "id": "Integer",
+  "node_id": "String",
+  "number": "Integer",
+  "title": "String",
+  "user": {
+    "login": "String",
+    "id": "Integer",
+    "node_id": "String",
+    "avatar_url": "String",
+    // ... (other user fields)
+    "site_admin": "Boolean"
+  },
+  "labels": [
+    // List of Structs
+    {
+      "name": "String",
+      "color": "String",
+      "id": "Integer"
+      // ... (other label fields)
+    }
+  ],
+  "state": "String",
+  "locked": "Boolean",
+  "assignee": "Null/Struct",
+  "assignees": [
+    // List of Structs (User objects)
+  ],
+  "milestone": "Null/Struct",
+  "comments": "Integer",
+  "created_at": "Timestamp",
+  "updated_at": "Timestamp",
+  "closed_at": "Timestamp/Null",
+  "author_association": "String",
+  "type": "String",
+  "active_lock_reason": "Null/String",
+  "draft": "Boolean",
+  "pull_request": {
+    "url": "String",
+    "html_url": "String",
+    "diff_url": "String",
+    "patch_url": "String",
+    "merged_at": "Timestamp/Null"
+  },
+  "body": "String",
+  "closed_by": "Null/Struct",
+  "reactions": {
+    "url": "String",
+    "total_count": "Integer"
+    // ... (other reaction counts)
+  },
+  "timeline_url": "String",
+  "performed_via_github_app": "Null",
+  "state_reason": "Null/String"
+}
+
+### Data Fields
+All original fields are retained except for milestone. This includes complex nested structures and all timestamps.
+
+id: int64. The unique GitHub identifier.
+
+number: int64. The sequential issue/PR number.
+
+title: string. The title of the issue/PR (Primary input).
+
+state: string. The current status (open or closed).
+
+comments: int32. The number of comments.
+
+created_at: timestamp. The creation time.
+
+updated_at: timestamp. The last update time.
+
+closed_at: timestamp. The closure time (null if open).
+
+user: struct. Metadata about the author.
+
+labels: list[struct]. A list of labels applied.
+
+pull_request: struct. Metadata specific to a Pull Request (includes merged_at timestamp).
+
+body: string. The main text description (Primary input).
+
+assignees: list[struct]. A list of assigned users.
+
+reactions: struct. Reaction counts (e.g., +1, heart).
+
+milestone: (DROPPED) This is the only field removed in normalization.
+
+### Data Splits
+
+Split Name,Sample Type,Number of Examples
+initial_fetch,Issues & PRs,"7,808"
+train,Pure Issues,"3,261"
+
+### Criteria for Splitting: 
+
+The data was collected as a single stream and is presented as one split (train).
+
+## Dataset Creation
+
+### Curation Rationale
+
+The dataset was curated to provide a high-quality corpus of pure issues for supervised learning. The primary motivation was to: 1) Separate Issues from PRs to avoid class confusion; 2) Augment Issues with Comments to provide the full conversational context necessary for realistic AI applications like automatic issue response or summarization.
+
+### Initial Data Collection and Normalization
+
+Process: Data was collected using the GitHub REST API (/repos/huggingface/datasets/issues) with state=all, resulting in 7,808 total records (issues and PRs).
+
+Separation: The initial records were filtered to include only records where the pull_request field was null, resulting in 3,261 issues.
+
+Augmentation: A subsequent fetch was performed to retrieve all associated comments for each of the 3,261 issues.
+
+Normalization: Only the milestone field was explicitly dropped prior to saving the .jsonl file. All other original fields were retained intact.
+
+### Who are the source language producers?
+
+The data was human-generated by developers, engineers, and community members interacting with the huggingface/datasets repository on GitHub.
+
+
+## Personal and Sensitive Information
+
+Fields like user contain publicly available GitHub login names and user IDs, which are considered personal identifiers.
+The raw text in the body field may contain indirect personal or sensitive information posted by users.
+
+## Considerations for Using the Data
+
+### Discussion of Biases
+
+The primary bias is Selection Bias: The data is specific to the datasets library and is heavily biased toward technical, engineering, and machine learning terminology.
+
+## Additional Information
+
+### Licensing Information
+
+The source data is derived from a public GitHub repository under the Apache-2.0 License.