nassimjp/Sindhi-Reasoning-Chat-Dataset

# 📘 **Sindhi‑Reasoning‑Chat‑Dataset**

A high‑quality, reasoning‑focused, instruction‑tuned conversational dataset for Sindhi (سنڌي), designed to support modern NLP research and LLM training for one of South Asia’s most underrepresented languages.

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## 🧠 **Dataset Summary**
Sindhi is a **low‑resource South Asian language** spoken by **over 30 million people**, primarily in Sindh, Pakistan. Despite its rich cultural and literary heritage, Sindhi has **very limited publicly available datasets** suitable for training modern large language models.

The **Sindhi‑Reasoning‑Chat‑Dataset** provides:

- Multi‑turn chat conversations  
- Reasoning‑oriented assistant responses  
- Clean system/user/assistant message structure  
- Native Sindhi text  
- High‑quality synthetic responses  
- Culturally accurate and linguistically correct content  

This dataset is ideal for **SFT**, **instruction tuning**, **reasoning tasks**, and **Sindhi chatbot development**.

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## 🌍 **Motivation**
Sindhi, like Pashto and Balochi, suffers from a severe lack of:

- Labeled datasets  
- Conversational corpora  
- Reasoning‑focused text  
- Instruction‑tuning material  

Modern LLMs require structured chat data, but Sindhi has almost none available publicly.  
This dataset aims to:

- Reduce the low‑resource gap  
- Enable Sindhi‑capable LLMs  
- Support multilingual and cross‑lingual research  
- Provide a foundation for Sindhi reasoning benchmarks  
- Encourage further dataset creation for South Asian languages  

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## 📜 **Attribution Notice (CC BY 4.0 Compliance)**  
This dataset uses *question text* derived from:

**Source Dataset:**  
**alinawazmahar/Sindhi_Sentiment_dataset**  
**License:** Creative Commons Attribution 4.0 International (CC BY 4.0)  
**Author:** Alina Nawaz Mahar  
**URL:** [https://huggingface.co/datasets/alinawazmahar/Sindhi_Sentiment_dataset](https://huggingface.co/datasets/alinawazmahar/Sindhi_Sentiment_dataset)

Only the **text field** was used as question seeds.  
All **assistant responses**, **reasoning**, **system prompts**, and **chat structures** are **newly generated** and **not part of the original dataset**.

To maintain license compatibility, this dataset is released under **CC BY 4.0**.

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## 📦 **Dataset Structure**
Each entry follows a consistent chat format:

### Fields
- **id** — unique integer  
- **messages** — list of chat messages  
  - **role** — system | user | assistant  
  - **content** — Sindhi text  

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## 🔍 **Data Sources**
- **User questions:** Derived from CC BY 4.0 licensed Sindhi_Sentiment_dataset  
- **Assistant responses:** Fully synthetic, reasoning‑oriented, culturally accurate  
- **System prompts:** Custom‑designed for Sindhi chat behavior  

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## 🧪 **Use Cases**
This dataset is suitable for:

- Sindhi chatbots  
- Instruction‑tuned LLMs  
- Reasoning and chain‑of‑thought modeling  
- Cultural and linguistic evaluation  
- Multilingual transfer learning  
- Benchmark creation  
- SFT / RLHF pipelines  

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## ⚖️ **Limitations**
- Synthetic responses may not represent all dialects  
- Dataset focuses on reasoning and chat, not general Sindhi corpus coverage  
- Cultural nuance is respected but may vary regionally  
- Should be combined with real Sindhi corpora for robust training  

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## 🛡️ **Ethical Considerations**
- No harmful, political, or biased content included  
- No real personal data  
- Designed for safe, culturally respectful model behavior  
- Attribution requirements of CC BY 4.0 are fully met  

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## 🔧 **Technical Notes**
- Format: JSONL  
- Encoding: UTF‑8  
- Compatible with:  
  - HuggingFace Transformers  
  - Unsloth Studio  
  - Talanda pipelines  
  - LMDB sharding  
  - SFT / RLHF frameworks  

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## 📜 **License**
This dataset is released under:

**Creative Commons Attribution 4.0 International (CC BY 4.0)**

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## 🏷️ **Tags**
- sindhi  
- low‑resource  
- south‑asian  
- reasoning  
- chat  
- instruction‑tuning  
- sft  
- multilingual  
- synthetic‑data  

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## 📈 **Benchmarks**
This dataset can be used to create:

- Sindhi reasoning benchmarks  
- Sindhi instruction‑following tests  
- Multilingual evaluation sets  
- Cross‑lingual transfer learning experiments  

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## 💻 **Example Usage**

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## 📚 **Citation**

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