Model Description
- Base Architecture: Qwen3-VL-8B-Instruct
- Fine-Tuning Method: QLoRA (PEFT)
- Language: Turkish
- Domain: High School Mathematics (12th Grade)
- Modality: Vision-Language (Image + Text → Text)
This model is a QLoRA fine-tuned version of Qwen3-VL-8B-Instruct trained on the Turkish-Math-VQA dataset, which consists of 12th-grade mathematics problems published by the Turkish Ministry of National Education (MEB). The model is designed to:
- Understand mathematical problem images
- Generate step-by-step solutions in Turkish
- Handle topics such as logarithms, sequences & series, trigonometry, derivatives, and integrals
Intended Use
Primary Use Cases
- Turkish mathematical Visual Question Answering (VQA)
- Educational AI assistants
- Step-by-step solution generation
- Math tutoring systems
- Research in Turkish multimodal reasoning
Out-of-Scope Use
- Professional exam grading without human validation
- Safety-critical mathematical applications
- Guaranteed mathematically verified reasoning
Training Data
Dataset: Turkish-Math-VQA The dataset contains mathematics problems from official 12th-grade exams prepared by the Turkish Ministry of National Education.
Dataset Fields:
test_number: The test identifierquestion_number: Question number within the testimage: The image containing the math problemsolution: Turkish solution generated synthetically using GPT-o1
Important Note on Labels:
The solution field was generated synthetically by GPT-o1 and has not been manually verified for correctness. While GPT-o1 is generally strong at solving problems at this level, the dataset may contain:
- Incorrect reasoning steps
- Logical inconsistencies
- Arithmetic mistakes
Therefore, the fine-tuned model may inherit these imperfections.
How to Get Started with the Model
from transformers import AutoProcessor, AutoModelForImageTextToText
processor = AutoProcessor.from_pretrained("khazarai/Math-VL-8B")
model = AutoModelForImageTextToText.from_pretrained("khazarai/Math-VL-8B")
messages = [
{
"role": "user",
"content": [
{"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"},
{"type": "text", "text": "Resimde verilen matematik problemini çözün."}
]
},
]
inputs = processor.apply_chat_template(
messages,
add_generation_prompt=True,
tokenize=True,
return_dict=True,
return_tensors="pt",
).to(model.device)
outputs = model.generate(**inputs, max_new_tokens=1024)
print(processor.decode(outputs[0][inputs["input_ids"].shape[-1]:]))
Citation
If you use this model in academic work, please cite:
- The original Qwen model
- Turkish-Math-VQA dataset
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