tokhey/Qwen2.5-3B-Egyptian-MCQ
tokhey/Qwen2.5-3B-Egyptian-MCQ is a 3.1 billion parameter Qwen2.5-3B-Instruct model fine-tuned by tokhey, specialized in generating English multiple-choice questions. It is specifically designed to mimic the style and structure of the Egyptian Ministry of Education's General Secondary Stage examinations. This model excels at producing curriculum-aligned grammar and vocabulary questions with structured JSON outputs, including explanations and plausible distractors.
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Overview
tokhey/Qwen2.5-3B-Egyptian-MCQ is a specialized fine-tuned version of the Qwen2.5-3B-Instruct model, developed by tokhey. It focuses on generating English multiple-choice questions (MCQs) that adhere to the specific style and difficulty of the Egyptian Ministry of Education's General Secondary Stage examinations. The model was instruction-tuned using LoRA (PEFT) on a synthetic dataset of approximately 6,400 samples, teaching it the structure and writing style of official Egyptian English assessments rather than memorizing questions.
Key Capabilities
- Generates Ministry-style English MCQs for grammar and vocabulary.
- Supports topic-based and unit-based generation, aligning with curriculum content.
- Outputs questions in a structured JSON format, including a statement, one correct answer, three plausible distractors, and an explanation for each question.
- Optimized for production deployment, with vLLM support recommended for inference.
Intended Use Cases
This model is ideal for:
- Educational platforms requiring authentic Egyptian Ministry-style English assessments.
- Automatic exam generation and curriculum-aware assessment systems.
- AI teaching assistants needing to create targeted English practice questions.
Limitations
- Specifically optimized for Egyptian secondary education English examinations.
- Outputs should always be reviewed by a human before official use.