---
language:
- ku
- ckb
- kmr
- hac
size_categories:
- 1B<n<10B
license: cc-by-4.0
pretty_name: KurCorpus 2B
tags:
- kurdish
- low-resource
- language-modeling
---

# KurCorpus 2B

![License: CC BY 4.0](https://img.shields.io/badge/License-CC%20BY%204.0-blue)
![Language: Kurdish (ckb/kmr/hac)](https://img.shields.io/badge/Language-Kurdish%20(ckb%2Fkmr%2Fhac)-informational)
![Size: 2B+ tokens](https://img.shields.io/badge/Size-2B%2B%20tokens-brightgreen)
[![DOI](https://img.shields.io/badge/DOI-10.17632%2Ffb5xhhn6m5.1-orange)](https://doi.org/10.17632/fb5xhhn6m5.1)

**KurCorpus 2B** is a multidialectal Kurdish text corpus (>2B tokens) for large-scale language modeling and downstream NLP.

- **Dialects:** Sorani (ckb), Kurmanji/Badini (kmr), Hawrami/Gorani (hac)  
- **License:** CC BY 4.0  
- **Repo:** https://huggingface.co/datasets/abdulhade/Kurdishcorpus  
- **External record:** Mendeley Data DOI `10.17632/fb5xhhn6m5.1`

---

## TL;DR

- Ready for **pretraining** and **finetuning** Kurdish LMs  
- Single field **`text`** (UTF-8), offered as large archives or sharded `.txt(.gz)`  
- Includes **normalization and cleaning** (Unicode, orthography, noise removal with placeholders like `[URL]`, `[EMAIL]`)  
- No official splits; create your own task-specific splits and report dialect coverage

---

## Quickstart

```python
from datasets import load_dataset

# Stream without downloading everything at once (recommended for very large corpora)
ds = load_dataset("abdulhade/Kurdishcorpus", split="train", streaming=True)

for i, ex in enumerate(ds.take(5)):
    print(ex["text"])
```
---
## cite
@dataset{rawf2025kurcorpus2b,
  title   = {KurCorpus 2B: A Multidialectal 2-Billion-Token Corpus for Kurdish Language Modeling},
  author  = {Rawf, Karwan Mahdi and Abdullah, Abdullah and Hussein, Amanj and Mohammed, Haukar},
  year    = {2025},
  version = {1},
  howpublished = {Mendeley Data},
  doi     = {10.17632/fb5xhhn6m5.1}
}