Khurram123/Shaheen-Gemma4-Urdu
Shaheen-Gemma4-Urdu is a 5.1 billion parameter Urdu language model developed by Khurram Pervez (Khurram123), fine-tuned on 51,686 high-quality Urdu instruction samples. Based on the Gemma 4 (2B) architecture, it provides deep linguistic understanding, formal vocabulary, and cultural nuance in Urdu. This model excels at handling complex Urdu grammar and literature, making it suitable for applications requiring high-fidelity Urdu text generation and comprehension.
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Overview
Shaheen-Gemma4-Urdu is a 5.1 billion parameter Urdu language model developed by Khurram Pervez (Khurram123). It is specifically fine-tuned on 51,686 high-quality Urdu instruction samples to achieve deep linguistic understanding, formal vocabulary, and cultural nuance in the Urdu language. The model is built upon the state-of-the-art Gemma 4 (2B) architecture and is available in both 16-bit Safetensors and Quantized GGUF formats.
Key Capabilities
- Exceptional Urdu Fluency: Tuned to handle complex Urdu grammar and formal literature with high precision.
- Efficient Performance: Delivers approximately 94 tokens per second on an NVIDIA RTX 4060 Ti, offering fast inference.
- Dual Format Availability: Provided as
model.safetensorsfortransformersandShaheen-Gemma4-Urdu-Q4_K_M.ggufforllama.cppintegration. - Strong Generalization: Achieved a final loss of 1.118 after approximately 2 hours of training (1 full epoch) on the
large-traversaal/urdu-instructdataset.
Good For
- Applications requiring high-fidelity Urdu text generation.
- Tasks involving complex Urdu grammar and formal literary understanding.
- Developers needing an efficient Urdu-specific LLM for deployment on-device or GPU-accelerated inference.