Update README.md

README.md

@@ -90,7 +90,24 @@ Ideal for:
 
 ## How to Use
 
-Below is a Python example on how to use the multilingual sentiment model:
+Using pipelines, it takes only 4 lines:
+
+```pyython
+from transformers import pipeline
+
+# Load the classification pipeline with the specified model
+pipe = pipeline("text-classification", model="tabularisai/multilingual-sentiment-analysis")
+
+# Classify a new sentence
+sentence = "I love this product! It's amazing and works perfectly."
+result = pipe(sentence)
+
+# Print the result
+print(result)
+```
+
+Below is a Python example on how to use the multilingual sentiment model without pipelines:
+
 
 ```python
 from transformers import AutoTokenizer, AutoModelForSequenceClassification