requirements.txt

transformers
torch
gradio

app.py

@@ -0,0 +1,25 @@
+import gradio as gr
+from transformers import T5Tokenizer, T5ForConditionalGeneration
+
+
+model_name = "cuneytkaya/fine-tuned-t5-small-turkish-mmlu"
+tokenizer = T5Tokenizer.from_pretrained(model_name)
+model = T5ForConditionalGeneration.from_pretrained(model_name)
+
+def generate_answer(question):
+    input_text = f"Soru: {question}"
+    inputs = tokenizer(input_text, return_tensors="pt")
+    outputs = model.generate(**inputs)
+    answer = tokenizer.decode(outputs[0], skip_special_tokens=True)
+    return answer
+
+# Gradio arayüzü
+interface = gr.Interface(
+    fn=generate_answer,
+    inputs="text",
+    outputs="text",
+    title="Turkish Exam Question Answering Model",
+    description="This model answers questions from Turkish academic exams like KPSS, TUS, etc.",
+)
+
+interface.launch()