Update README.md

README.md

@@ -22,9 +22,12 @@ In this dataset, given a tweet, the goal was to infer the underlying topic of th
  
 ```python
 from transformers import AutoTokenizer, AutoModelForSequenceClassification, pipeline
+
 tokenizer = AutoTokenizer.from_pretrained("Monsia/camembert-fr-covid-tweet-sentiment-classification")
 model = AutoModelForSequenceClassification.from_pretrained("Monsia/camembert-fr-covid-tweet-sentiment-classification")
+
 nlp_topic_classif = transformers.pipeline('topics-classification', model = model, tokenizer = tokenizer)
 nlp_topic_classif("tchai on est morts. on va se faire vacciner et ils vont contrôler comme les marionnettes avec des fils. d'après les '' ont dit ''...")
+
 # Output: [{'label': 'opinions', 'score': 0.831]
 ```