Create README.md

README.md

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+license: apache-2.0
+language:
+- ps
+tags:
+- reasoning
+- sft
+- pashto
+- logic
+- math
+pretty_name: Qwopus Pashto Reasoning SFT Dataset
+size_categories:
+- 10k<n<100k
+---
+
+# 🚀 Qwopus Pashto Reasoning SFT Dataset
+
+This is a meticulously curated, high-quality Supervised Fine-Tuning (SFT) dataset tailored specifically for training **Pashto Natural Language Processing (NLP)** models with deep reasoning, mathematical, logical, and structural capabilities. 
+
+The dataset contains a carefully processed mix of interactive human-assistant dialogues, optimized for high token fidelity and cultural/linguistic alignment.
+
+## 📊 Dataset Summary
+
+- **Repository Owner:** Nassim (`nassimjp`)
+- **Total Records:** 23,500+ Unique Conversations
+- **Language:** Native Pashto (پښتو)
+- **Primary Use Case:** Instruction Fine-Tuning (SFT) for Reasoning & Cognitive LLMs
+- **License:** Apache 2.0
+
+## 🗂️ Data Structure
+
+Each record follows a clean, standardized conversational schema compatible with modern training frameworks (such as LLaMA-Factory, Axolotl, and Hugging Face Transformers):
+
+```json
+{
+  "conversations": [
+    {
+      "from": "system",
+      "value": "System prompt defining the model's persona and logic constraint."
+    },
+    {
+      "from": "human",
+      "value": "Instruction or reasoning problem in Pashto."
+    },
+    {
+      "from": "gpt",
+      "value": "Detailed, step-by-step reasoning output or formatting in Pashto."
+    }
+  ]
+}
+
+```
+
+## 🧹 Curation & Quality Engineering
+
+* **Atomic Deduplication:** Built using customized MD5 cryptographic hashing pipelines to guarantee absolute uniqueness across all training instances.
+* **Smart Chunking:** Text blocks are contextually managed under safe token lengths (`max_chars=4000`) to maintain paragraph cohesion and native Pashto grammar alignment.
+* **Cognitive Diversity:** Includes structural parsing, linguistic identification, visual-spatial grouping simulations (using advanced emoji patterning), and local market mathematical reasoning.
+
+## 🚀 Citation & Usage
+
+If you utilize this dataset in your research or LLM training cycles, please credit the repository as follows:
+
+```bibtex
+@misc{qwopus-pashto-reasoning-sft,
+  author     = {Nassim (nassimjp)},
+  title      = {Qwopus Pashto Reasoning SFT Dataset},
+  year      = {2026},
+  publisher = {Hugging Face},
+  journal   = {Hugging Face Datasets},
+  howpublished = {\url{[https://huggingface.co/datasets/nassimjp/qwopus-pashto-reasoning-sft](https://huggingface.co/datasets/nassimjp/qwopus-pashto-reasoning-sft)}}
+}
+
+```
+## 🗺️ Provenance & Adaptation
+This dataset is a translated, optimized, and adapted version of [kalomaze/Opus_Instruct_3k](https://huggingface.co/datasets/kalomaze/Opus_Instruct_3k). It has been structurally modified, cleaned from duplicates using cryptographic hashing, and tailored to meet high-fidelity native Pashto reasoning and instruction-following requirements.