Khurram123/Qwen2.5-3B-Urdu-Ultimate-Poet
Khurram123/Qwen2.5-3B-Urdu-Ultimate-Poet is a 3.1 billion parameter language model developed by Khurram Pervez, based on the Qwen2.5-3B architecture with a 32768 token context length. This specialized model is fine-tuned for the Urdu language, excelling in news summarization, instruction following, and particularly in generating classical and modern Urdu poetry. Its primary use case is generating nuanced Urdu text across various domains, with a strong emphasis on poetic composition.
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Qwen2.5-3B-Urdu-Ultimate-Poet: A Specialized Urdu LLM
Developed by Khurram Pervez (Khurram123), this model is a highly specialized version of the Qwen2.5-3B architecture, meticulously fine-tuned for the Urdu language. It leverages a multi-stage training process to achieve versatility across several Urdu-specific tasks.
Key Capabilities
- Urdu News & Information Summarization: Trained on the XL-Sum dataset to provide accurate and concise summaries of complex Urdu news articles.
- Urdu Instruction Following & Chat: Integrated with Urdu-Alpaca data, enabling it to follow user commands, answer questions, and engage in natural conversations in Urdu.
- Classical & Modern Urdu Poetry Generation: Deeply fine-tuned on the Urdu-Poetry-Dataset, allowing it to compose ghazals and nazms with an understanding of Urdu poetic rhythm, vocabulary, and various styles (e.g., Firaq Gorakhpuri).
Good for
- Generating high-quality, contextually relevant Urdu text.
- Summarizing Urdu news and informational content.
- Developing Urdu-speaking chatbots and conversational AI.
- Creating original Urdu poetry, including ghazals and nazms.
- Applications requiring nuanced understanding and generation of the Urdu language, especially in creative writing and information processing.