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Khurram123/urdu-poetry-mega-corpus

📜 Urdu Poetry Mega Corpus This dataset is a comprehensive collection of classical and modern Urdu poetry, meticulously curated for training Large Language Models (LLMs) like Qwen, Llama, and Mistral to generate authentic Urdu Ghazals and Nazms. 🌟 Dataset Overview The Urdu Poetry Mega Corpus contains over 42,639 high-quality Urdu couplets (ash'aar). It is designed to capture the structural nuances, rhythmic patterns (Beher), and stylistic essence of renowned… See the full description on the dataset page: https://huggingface.co/datasets/Khurram123/urdu-poetry-mega-corpus.

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Dataset Card

📜 Urdu Poetry Mega Corpus

This dataset is a comprehensive collection of classical and modern Urdu poetry, meticulously curated for training Large Language Models (LLMs) like Qwen, Llama, and Mistral to generate authentic Urdu Ghazals and Nazms.

🌟 Dataset Overview

The Urdu Poetry Mega Corpus contains over 42,639 high-quality Urdu couplets (ash'aar). It is designed to capture the structural nuances, rhythmic patterns (Beher), and stylistic essence of renowned poets such as Ahmad Faraz, Mirza Ghalib, Allama Iqbal, and others.

  • —Total Couplets: 42,639
  • —Format: CSV / JSON
  • —Primary Use: Fine-tuning LLMs, Poetry Generation, Rhyme Analysis, and Sentiment Analysis.

📊 Dataset Structure

Each entry in the dataset consists of the following features:

ColumnDescriptionExample
misra1The first line of the couplet (Misra-e-Oola).ہم نے اک عمر بسر کی ہے غمِ یار کے ساتھ
misra2The second line of the couplet (Misra-e-Sani).جیسے اک لمحہ گزرا ہو کسی پیار کے ساتھ
poetThe name of the poet (for style guidance).Ahmad Faraz
genreThe type of poetry (Ghazal/Nazm).Ghazal

🚀 Key Applications

  1. 1.Poetry Generation: Fine-tuning models (like Qwen2.5-7B) to complete couplets or write full Ghazals.
  2. 2.Style Mimicry: Training models to write in the specific diction of a particular poet.
  3. 3.NLP Research: Analyzing the meter (Beher) and rhyme (Radeef/Qafiya) of Urdu literature.

🛠️ How to Use with Hugging Face datasets

You can easily load this dataset using the Hugging Face library:

python
from datasets import load_dataset

dataset = load_dataset("Khurram123/urdu-poetry-mega-corpus")

# Preview the first entry
print(dataset['train'][0])