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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.

sourceHugging Faceapache-2.0updated 1mo agoView on Hugging Face
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Dataset Card

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:

json
{
  "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

python
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 ---