Create app.py

app.py

@@ -0,0 +1,21 @@
+from transformers import T5ForConditionalGeneration, T5Tokenizer
+
+# Load the model and tokenizer
+model = T5ForConditionalGeneration.from_pretrained("miiiciiii/I-Comprehend_qg")
+tokenizer = T5Tokenizer.from_pretrained("miiiciiii/I-Comprehend_qg")
+
+def get_question(context, answer, model, tokenizer):
+    """Generate a question for the given answer and context."""
+    answer_span = context.replace(answer, f"<hl>{answer}<hl>", 1) + "</s>"
+    inputs = tokenizer(answer_span, return_tensors="pt")
+    question = model.generate(input_ids=inputs.input_ids, max_length=50)[0]
+
+    return tokenizer.decode(question, skip_special_tokens=True)
+
+# Define the context and answer
+context = "The Eiffel Tower is located in Paris and is one of the most famous landmarks in the world."
+answer = "Eiffel Tower"
+
+# Generate the question
+question = get_question(context, answer, model, tokenizer)
+print("Generated Question:", question)