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Model: tokhey/egyptian-mcq-generator-mistral-7b
Source: Original Platform

README.md

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+---
+license: apache-2.0
+base_model: mistralai/Mistral-7B-Instruct-v0.3
+library_name: transformers
+pipeline_tag: text-generation
+language:
+- en
+tags:
+- mistral
+- instruction-tuned
+- lora
+- unsloth
+- education
+- english
+- mcq
+- egyptian-ministry
+---
+
+# Egyptian MCQ Generator - Mistral 7B Instruct
+
+This repository contains a LoRA fine-tuned version of **mistralai/Mistral-7B-Instruct-v0.3** for generating English multiple-choice questions that follow the official Egyptian Ministry of Education examination style.
+
+## Model Information
+
+- Base Model: mistralai/Mistral-7B-Instruct-v0.3
+- Fine-tuning: LoRA (PEFT)
+- Framework: Unsloth
+- Language: English
+- Task: Instruction Fine-Tuning
+
+## Training Configuration
+
+| Parameter | Value |
+|-----------|-------|
+| LoRA Rank | 16 |
+| LoRA Alpha | 32 |
+| Dropout | 0.05 |
+| Learning Rate | 1e-4 |
+| Epochs | 3 |
+| Max Sequence Length | 2048 |
+
+## Example
+
+```python
+from transformers import AutoTokenizer, AutoModelForCausalLM
+import torch
+
+model_name = "tokhey/egyptian-mcq-generator-mistral-7b"
+
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+
+model = AutoModelForCausalLM.from_pretrained(
+    model_name,
+    torch_dtype=torch.float16,
+    device_map="auto",
+)
+
+messages = [
+    {
+        "role": "system",
+        "content": (
+            "You are a Senior English Assessment Specialist. "
+            "Generate official Egyptian Ministry of Education English MCQs. "
+            "Return valid JSON only."
+        ),
+    },
+    {
+        "role": "user",
+        "content": (
+            "Generate 10 official Egyptian Ministry English MCQs "
+            "about Past Perfect / Past Perfect Continuous."
+        ),
+    },
+]
+
+text = tokenizer.apply_chat_template(
+    messages,
+    tokenize=False,
+    add_generation_prompt=True,
+)
+
+inputs = tokenizer(
+    text,
+    return_tensors="pt",
+).to(model.device)
+
+outputs = model.generate(
+    **inputs,
+    max_new_tokens=1500,
+    temperature=0.7,
+)
+
+print(
+    tokenizer.decode(
+        outputs[0][inputs.input_ids.shape[1]:],
+        skip_special_tokens=True,
+    )
+)
+```
+
+## Output Format
+
+```json
+{
+    "statement": "...",
+    "correct_answer": "...",
+    "plausible_distractors": [
+        "...",
+        "...",
+        "..."
+    ],
+    "explanation": "..."
+}
+```
+
+## License
+
+This model is derived from **mistralai/Mistral-7B-Instruct-v0.3** and follows the original Mistral model license.