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IQRA-AI/
gemma-3-4b-Quran-1epochs

Name: gemma-3-4b-Quran-1epochs
Availability: InStock

safetensors

gemma3

question-answering

emhaihsan/quran-indonesia-tafseer-translation

google/gemma-3-4b-it

finetune

gemma

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IQRA-AI/gemma-3-4b-Quran-1epochs

Model Description

IQRA-AI/gemma-3-4b-Quran-1epochs is a fine-tuned version of the Gemma 3 4B model that has been specifically trained on Quranic content. This model has been fine-tuned for 1 epoch on a dataset consisting of Quranic knowledge, making it capable of providing information about the Quran, its chapters (surahs), verses (ayat), and related Islamic topics.

Use Cases

This model is designed to:

Answer questions about the Quran
Provide information about the revelation of Quranic chapters
Explain Quranic verses and their meanings
Share knowledge about Islamic principles derived from the Quran

Limitations

The model has been trained for just 1 epoch, so its knowledge might not be as comprehensive as more extensively trained models
As with any language model, outputs should be verified against authentic Islamic sources
The model may occasionally generate inaccurate information

Usage

Installation

pip install transformers accelerate torch

Inference Example

python

from transformers import AutoProcessor, Gemma3ForConditionalGeneration
import torch

model_id = "IQRA-AI/gemma-3-4b-Quran-1epochs"

model = Gemma3ForConditionalGeneration.from_pretrained(
    model_id, device_map="auto"
).eval()

processor = AutoProcessor.from_pretrained(model_id)

messages = [
    {
        "role": "system",
        "content": [{"type": "text", "text": ""}]
    },
    {
        "role": "user",
        "content": [
            {"type": "text", "text": "Surah Al Fatihah turun dimana?"}
        ]
    }
]

inputs = processor.apply_chat_template(
    messages, add_generation_prompt=True, tokenize=True,
    return_dict=True, return_tensors="pt"
).to(model.device, dtype=torch.bfloat16)

input_len = inputs["input_ids"].shape[-1]

with torch.inference_mode():
    generation = model.generate(**inputs, max_new_tokens=100, do_sample=False)
    generation = generation[0][input_len:]

decoded = processor.decode(generation, skip_special_tokens=True)
print(decoded)

Model Training

Base model: Gemma 3 4B
Training dataset: emhaihsan/quran-indonesia-tafseer-translation with 24,700 samples
Training epochs: 5% of the Dataset x 8 Epochs
Batch size: 8

License

This model is subject to the Gemma 3 license. Please ensure you follow all licensing requirements when using this model.

Citation

If you use this model in your research or applications, please cite:

@misc{iqra-ai-gemma-3-4b-quran,
  author = {IQRA-AI},
  title = {Gemma 3 4B Quran 1 Epoch},
  year = {2025},
  publisher = {Hugging Face},
  author = {Ariel Fikru Avicenna}
  howpublished = {\url{https://huggingface.co/IQRA-AI/gemma-3-4b-Quran-1epochs}}
}

Contact

For questions, suggestions, or issues related to this model, please contact us through the Hugging Face model repository.