Update README.md

README.md

@@ -59,17 +59,15 @@ model = AutoModelForQuestionAnswering.from_pretrained(model)
 qa_pipeline = pipeline("question-answering", model=model, tokenizer=tokenizer)
 
 # Example usage
-context = "CONTEXT"
+context = "شرکت فولاد مبارکه در سال 1371 تأسیس شد."
 
-question = "QUESTION"
+question = "چه زمانی شرکت فولاد مبارکه تأسیس شد؟"
 
-# Modify the pipeline to return more answers
-results = qa_pipeline(question=question, context=context, top_k=5)  # top_k specifies the number of answers
-
-# Display the answers
-for idx, result in enumerate(results):
-    print(f"Answer {idx+1}: {result['answer']}")
+# Modify the pipeline to return answer
+results = qa_pipeline(question=question, context=context)
 
+# Display the answer
+print(results['answer'])
 ```
 
 ## Datasets