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nassimjp/Liquid-Urdu-Reasoning-Chat-Dataset

Liquid Urdu Reasoning Chat Dataset This dataset contains high-quality, synthetically generated Urdu conversational and reasoning data designed for Supervised Fine-Tuning (SFT) of Small Language Models (SLMs), specifically optimized for reasoning models like those run via llama.cpp using DeepSeek-style reasoning formats. Dataset Structure The dataset is formatted in JSONL where each line contains chat history including system prompts, user queries, model… See the full description on the dataset page: https://huggingface.co/datasets/nassimjp/Liquid-Urdu-Reasoning-Chat-Dataset.

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Dataset Card

Liquid Urdu Reasoning Chat Dataset

This dataset contains high-quality, synthetically generated Urdu conversational and reasoning data designed for Supervised Fine-Tuning (SFT) of Small Language Models (SLMs), specifically optimized for reasoning models like those run via llama.cpp using DeepSeek-style reasoning formats.

Dataset Structure

The dataset is formatted in JSONL where each line contains chat history including system prompts, user queries, model thinking/reasoning blocks (<think>), and final responses in fluent standard Urdu script.

json

{
  "messages": [
    {"role": "system", "content": "You are a helpful AI assistant..."},
    {"role": "user", "content": "..."},
    {"role": "assistant", "content": "<think>\n...\n</think>\n\n..."}
  ]
}

Use Cases

—Fine-Tuning Urdu Chatbots: Training models to converse fluently in standard Urdu script while adhering to polite, culturally aware system guidelines.
—Reasoning Distillation: Training SLMs to output structured chain-of-thought (<think>) reasoning prior to delivering final outputs.
—Conversational AI Enhancement: Adapting edge cases and classification-style datasets into rich conversational data.

License

This project is open-source and licensed under the MIT License.

MIT License

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