| from transformers import T5Tokenizer, T5ForConditionalGeneration | |
| # Load the model and tokenizer | |
| model_name = "t5-base" # lightweight and works offline | |
| tokenizer = T5Tokenizer.from_pretrained(model_name) | |
| model = T5ForConditionalGeneration.from_pretrained(model_name) | |
| def generate_mcqs(text, num_questions=3): | |
| input_text = f"generate questions: {text}" | |
| input_ids = tokenizer.encode(input_text, return_tensors="pt", max_length=512, truncation=True) | |
| outputs = model.generate( | |
| input_ids=input_ids, | |
| max_length=256, | |
| num_return_sequences=1, | |
| temperature=0.7 | |
| ) | |
| decoded = tokenizer.decode(outputs[0], skip_special_tokens=True) | |
| return decoded.strip() | |
| # 🔽 TEST EXAMPLE 🔽 | |
| if __name__ == "__main__": | |
| sample = """ | |
| The process of photosynthesis allows plants to convert sunlight, water, and carbon dioxide into food. This process takes place in the chloroplasts and releases oxygen as a byproduct. | |
| """ | |
| print("📘 Quiz Output:\n") | |
| print(generate_mcqs(sample)) | |