Create Edraky AI!

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<img src="https://cdn-uploads.huggingface.co/production/uploads/686e726239f003427404a1be/uuB7LFKDX1C5B28DGJyZN.png" alt="Edraky Logo" width="200"/>
</p>

# 🧠 إدراكي (Edraky) — Multilingual Educational AI Assistant

**إدراكي (Edraky)** is a multilingual AI model designed to support students with interactive learning, question-answering, and intelligent content generation across **Arabic**, **English**, and **Hebrew**. It is especially focused on **educational content** for middle-school learners, including subjects like Social Studies, Arabic Language, and more.

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## 🧾 Model Details

- **Languages**: Arabic, English, Hebrew
- **License**: Apache 2.0
- **Base Model**: `Qwen/Qwen2-1.5B-Instruct`
- **Library**: `transformers`
- **Pipeline Tag**: `text-generation`
- **Trained on**:
- `rosoft/rStar-Coder`
- `gsm8k-rerun/Qwen_Qwen2.5-1.5B-Instruct`
- **Tags**: `multilingual`, `educational`, `fine-tuned`, `arabic`, `hebrew`, `qwen`, `student-assistant`

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## 🎯 Use Cases

- 📚 **AI Study Assistant**: Helps students with curriculum-based questions
- 🧠 **Educational Content Creation**: Generates quiz questions, summaries, and explanations
- 🌐 **Language Support**: Understands and responds in Arabic, English, and Hebrew
- 👨‍🏫 **Teacher Support**: Generates model answers, revision notes, and more

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## 🔍 Evaluation Metrics

| Metric | Value |
|------------|-------|
| Accuracy | ✅ High (on educational QA datasets) |
| BLEU Score | 🧪 Coming Soon |
| F1 Score | 🧪 Coming Soon |

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## 📚 Training Datasets

The model was fine-tuned on high-quality datasets including:

- [`rosoft/rStar-Coder`](https://huggingface.co/datasets/rosoft/rStar-Coder)
- [`gsm8k-rerun/Qwen_Qwen2.5-1.5B-Instruct`](https://huggingface.co/datasets/gsm8k-rerun/Qwen_Qwen2.5-1.5B-Instruct)

Additional in-house educational data tailored for Egyptian curricula was used to optimize performance.

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## 🚀 How to Use

You can try it with the Hugging Face Inference API or use it directly via Transformers:

```python
from transformers import AutoModelForCausalLM, AutoTokenizer

model_id = "your-username/edraky-ai"
tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(model_id)

inputs = tokenizer("اشرح درس الثورة العرابية", return_tensors="pt")
outputs = model.generate(**inputs, max_new_tokens=200)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))
💡 Intended Uses
This model is designed to be:

🧑‍🎓 Student-friendly

👩‍🏫 Useful for teachers and educators

🌐 Ready for multilingual educational tasks

⚠️ Limitations
This model is not a replacement for a certified teacher.

Knowledge is limited to the data it was trained on.

May hallucinate or generate incorrect facts; always verify educational material.

🤝 Contributing
We're open to collaboration, dataset contributions, or feedback to improve this model further for educational use in the Arab world and beyond.

🧾 License
Apache License 2.0 — Free to use, share, and modify with attribution.

README.md

@@ -1,3 +1,26 @@
----
-license: apache-2.0
----
+---
+license: apache-2.0
+datasets:
+- fka/awesome-chatgpt-prompts
+- microsoft/rStar-Coder
+- gsm8k-rerun/Qwen_Qwen2.5-1.5B-Instruct
+language:
+- ar
+- en
+- he
+metrics:
+- accuracy
+- perplexity
+- wer
+base_model:
+- Qwen/Qwen2-1.5B-Instruct
+pipeline_tag: text-generation
+library_name: transformers
+tags:
+- multilingual
+- arabic
+- hebrew
+- qwen
+- educational
+- fine-tuned
+---