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README.md
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- **Arabic-First Design**: Built from the ground up to excel at understanding and generating high-quality Arabic text
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- **Enhanced Reasoning**: Specialized in step-by-step problem solving, particularly for mathematical questions
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- **Optimized Performance**: Accelerated using Unsloth for faster inference and reduced computational requirements
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- **GRPO Implementation**: Utilizes
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## Usage Example
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- Base architecture fine-tuned on diverse Arabic datasets
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- GRPO (Generalized Reinforced Preference Optimization) for better alignment
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- Specialized training on mathematical reasoning and step-by-step problem
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## Performance
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ALLaM-Thinking demonstrates strong capabilities in:
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- Mathematical problem
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- Logical analysis and deduction
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- Maintaining coherence in long-form responses
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- Domain-specific reasoning in technical fields
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## Limitations
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- Model outputs should always be verified by human experts, especially for critical applications
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- May occasionally produce incorrect mathematical reasoning despite step-by-step approach
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- Limited context window compared to some larger models
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- Performance may vary based on query complexity and domain specificity
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```bibtex
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@misc{almaghrabima2025allam,
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author = {Al-
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title = {ALLaM-Thinking: Arabic Large Language Model with Enhanced Reasoning Capabilities},
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year = {2025},
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publisher = {Hugging Face},
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- **Arabic-First Design**: Built from the ground up to excel at understanding and generating high-quality Arabic text
|
| 21 |
- **Enhanced Reasoning**: Specialized in step-by-step problem solving, particularly for mathematical questions
|
| 22 |
- **Optimized Performance**: Accelerated using Unsloth for faster inference and reduced computational requirements
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- **GRPO Implementation**: Utilizes Group Relative Policy Optimization for improved alignment
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## Usage Example
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| 26 |
|
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| 79 |
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| 80 |
- Base architecture fine-tuned on diverse Arabic datasets
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| 81 |
- GRPO (Generalized Reinforced Preference Optimization) for better alignment
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| 82 |
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- Specialized training on mathematical reasoning and step-by-step problem-solving
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| 83 |
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## Performance
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ALLaM-Thinking demonstrates strong capabilities in:
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| 87 |
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| 88 |
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- Mathematical problem-solving with step-by-step reasoning
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- Logical analysis and deduction
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| 90 |
- Maintaining coherence in long-form responses
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| 91 |
- Domain-specific reasoning in technical fields
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|
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## Limitations
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| 94 |
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| 95 |
- Model outputs should always be verified by human experts, especially for critical applications
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| 96 |
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- May occasionally produce incorrect mathematical reasoning despite the step-by-step approach
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| 97 |
- Limited context window compared to some larger models
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| 98 |
- Performance may vary based on query complexity and domain specificity
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```bibtex
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@misc{almaghrabima2025allam,
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author = {Mohammed Al-Maghrabi Research},
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title = {ALLaM-Thinking: Arabic Large Language Model with Enhanced Reasoning Capabilities},
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year = {2025},
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publisher = {Hugging Face},
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