Update README.md

README.md

@@ -23,6 +23,18 @@ print(model(**tokenized).logits)
 # returns scores 0.8409 and 0.2601 for the two candidates
 ```
 
+### Use with pipeline
+```python
+from transformers import pipeline
+
+pipe = pipeline("text-classification", model="tum-nlp/NegBLEURT")
+pairwise_input = [
+  [["Ray Charles is legendary.", "Ray Charles is a legend."]],
+  [["Ray Charles is legendary.", "Ray Charles isn’t legendary."]]
+]
+print(pipe(pairwise_input, function_to_apply="none"))
+# returns [{'label': 'NegBLEURT_score', 'score': 0.8408917784690857}, {'label': 'NegBLEURT_score', 'score': 0.26007288694381714}]
+```
 
 ## Training Details