nassimjp/Pashto-Clean-100k-Pairs.QA
Pashto‑Clean‑100k‑Pairs.QA A curated collection of 100,000 Pashto question–answer pairs, cleaned and normalized for general‑purpose Pashto NLP training.This dataset focuses on broad coverage, topic diversity, and clean formatting, without synthetic reasoning or long‑context generation. Dataset Summary Pashto-Clean-100k-Pairs.QA contains short, direct QA pairs across 70+ everyday topics: Daily life Community Education Work Nature Safety Culture… See the full description on the dataset page: https://huggingface.co/datasets/nassimjp/Pashto-Clean-100k-Pairs.QA.
Pashto‑Clean‑100k‑Pairs.QA
A curated collection of 100,000 Pashto question–answer pairs, cleaned and normalized for general‑purpose Pashto NLP training. This dataset focuses on broad coverage, topic diversity, and clean formatting, without synthetic reasoning or long‑context generation.
Dataset Summary
Pashto-Clean-100k-Pairs.QA contains short, direct QA pairs across 70+ everyday topics:
- Daily life
- Community
- Education
- Work
- Nature
- Safety
- Culture
- Religion & ethics
- Finance
- Agriculture
- Technology
- Public services
- Children & learning
- Local storytelling
- And more
Each entry follows a simple JSON structure:
{
"question": "...",
"answer": "..."
}Data Characteristics
- Total pairs: ~100,000
- Format: JSONL
- Language: Pashto
- Average line length: short
- Long lines (>1024 chars): ~750
- Short lines (<512 chars): majority of dataset
This dataset is intentionally clean and compact, suitable for lightweight QA training.
Use Cases
- Pashto QA models
- Pashto chatbot base training
- Pashto text classification
- Pashto retrieval‑augmented systems
- Pashto topic modeling
- Pashto semantic search
- Pashto embedding training
🚨 Important Limitations
This dataset is NOT suitable for:
- SFT on reasoning
- Instruction‑following with depth
- Long‑context training
- Multi‑turn conversation modeling
- Chain‑of‑thought Pashto LLMs
The dataset consists mostly of short answers, originally generated by a low‑quality model, and therefore lacks:
- multi‑paragraph reasoning
- deep explanations
- structured thought
- long contextual chains
You need longer, richer, deeper Pashto data for reasoning‑capable LLMs.
Recommended Extensions
To build a high‑quality Pashto LLM, consider adding:
- Long‑form synthetic reasoning data
- Multi‑turn dialogues
- Chain‑of‑thought expansions
- Topic‑specific deep explanations
- Real‑world Pashto text corpora
Loading the Dataset
from datasets import load_dataset
ds = load_dataset("nassimjp/Pashto-Clean-100k-Pairs.QA")License
Released for research and Pashto NLP development. Please review license terms before production use.
Author
Dataset created and maintained by NASIMJP. Dataset is based on junaid008/Pashto-100k-Pairs ---
