added pipeline usage example

README.md

@@ -75,3 +75,18 @@ result2 = predict_sentiment("I really disliked this movie, it was terrible.")
 
 print(f"Sentiment: {result1['sentiment']}, Confidence: {result1['confidence']}%")
 print(f"Sentiment: {result2['sentiment']}, Confidence: {result2['confidence']}%")
+
+
+
+from transformers import pipeline
+
+pipe = pipeline("text-classification", model="philipobiorah/bert-imdb-model")
+
+text_to_classify = "This movie was fantastic! I loved every minute of it."
+result = pipe(text_to_classify)
+print(result)
+
+text_to_classify_2 = "The acting was terrible and the plot made no sense."
+result_2 = pipe(text_to_classify_2)
+print(result_2)
+