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, 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
- Dataset: Arabic LLaMA Math Dataset
- Number of Parameters: 3 billion
- Fine-tuned by: 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:
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 = "ู
ุง ูู ู
ุฌู
ูุน ุงูุฒูุงูุง ูู ู
ุซูุซุ" # 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:
@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.
Model tree for Jr23xd23/Math_Arabic_Llama-3.2-3B-Instruct
Base model
meta-llama/Llama-3.2-3B-Instruct