README.md

---
language:
- ar
tags:
- llama
- text-generation
- instruct
- arabic
- math
- fine-tuned
datasets:
- Jr23xd23/Arabic_LLaMA_Math_Dataset
license: apache-2.0
base_model: meta-llama/Llama-3.2-3B-Instruct
pipeline_tag: text-generation
inference: true
---

# Math_Arabic_Llama-3.2-3B-Instruct

## Model Description

**Math_Arabic_Llama-3.2-3B-Instruct** is a fine-tuned version of the **Llama-3.2-3B-Instruct** model, tailored for solving mathematical problems in Arabic. The model was trained using the **[Arabic LLaMA Math Dataset](https://github.com/jaberjaber23/Arabic-LLaMA-Math-Dataset)**, which includes a wide range of mathematical problems in natural language (Arabic). This model is ideal for educational applications, tutoring, and systems that require automatic math problem-solving in Arabic.

## Model Details

- **Model Type**: Transformer-based language model fine-tuned for text generation
- **Languages**: Arabic
- **Base Model**: [meta-llama/Llama-3.2-3B-Instruct](https://huggingface.co/meta-llama/Llama-3.2-3B-Instruct)
- **Dataset**: [Arabic LLaMA Math Dataset](https://github.com/jaberjaber23/Arabic-LLaMA-Math-Dataset)
- **Number of Parameters**: 3 billion
- **Fine-tuned by**: [Jr23xd23](https://huggingface.co/Jr23xd23)

## Training Data

The model was fine-tuned on the **Arabic LLaMA Math Dataset**, which consists of 12,496 examples covering various mathematical topics, such as:

- Basic Arithmetic
- Algebra
- Geometry
- Probability
- Combinatorics

Each example in the dataset includes:
- **Instruction**: The problem statement in Arabic
- **Solution**: The solution to the problem in Arabic

## Intended Use

### Primary Use Cases:

- Solving mathematical problems in Arabic
- Educational applications
- Tutoring systems for Arabic-speaking students
- Mathematical reasoning tasks in Arabic

### How to Use

You can use the model in Python with the Hugging Face transformers library:

```python
from transformers import AutoModelForCausalLM, AutoTokenizer

tokenizer = AutoTokenizer.from_pretrained("Jr23xd23/Math_Arabic_Llama-3.2-3B-Instruct")
model = AutoModelForCausalLM.from_pretrained("Jr23xd23/Math_Arabic_Llama-3.2-3B-Instruct")

# Example: Solving a math problem in Arabic
input_text = "ما هو مجموع الزوايا في مثلث؟" # What is the sum of angles in a triangle?
inputs = tokenizer(input_text, return_tensors="pt")
output = model.generate(**inputs, max_length=100)
print(tokenizer.decode(output[0], skip_special_tokens=True))
```

## Limitations

- The model is not designed for non-mathematical language tasks.
- Performance may degrade when applied to highly complex mathematical problems beyond the scope of the training dataset.
- The model's outputs should be verified for critical applications.

## License

This model is licensed under the **Apache 2.0 License**.

## Citation

If you use this model in your research or projects, please cite it as follows:

```bibtex
@model{Math_Arabic_Llama_3.2_3B_Instruct,
  title={Math_Arabic_Llama-3.2-3B-Instruct},
  author={Jr23xd23},
  year={2024},
  publisher={Hugging Face},
  url={https://huggingface.co/Jr23xd23/Math_Arabic_Llama-3.2-3B-Instruct},
}
```

## Acknowledgements

Special thanks to the creators of the **Arabic LLaMA Math Dataset** for providing a rich resource for fine-tuning the model.