Update README.md

README.md

@@ -10,23 +10,23 @@ This model predicts sentiment for German text.
 
 To use this model, first set it up:
 
-'''python
+```python
 # if necessary:
 # pip install transformers
 from transformers import pipeline
 
 sentiment_model = pipeline(model=aari1995/German_Sentiment)
-'''
+```
 
 to use it:
 
-'''python
+```python
 sentence = ["Ich liebe die Bahn. Pünktlich wie immer ... -.-","Meine Beschwerde wurde super abgewickelt"]
 result = sentiment_model(sentence)
 print(result)
 #Output:
 #[{'label': 'negative', 'score': 0.4935680031776428},{'label': 'positive', 'score': 0.4388483762741089}]
-'''
+```
 
 Credits / Special Thanks:
 This model was fine-tuned by Aaron Chibb. It is trained on [twitter dataset by tygiangz](https://huggingface.co/datasets/tyqiangz/multilingual-sentiments) and based on gBERT-large by [deepset](https://huggingface.co/deepset/gbert-large).