Update README.md

README.md

@@ -31,7 +31,7 @@ Then you can use the model like this:
 
 ```python
 from sentence_transformers import SentenceTransformer
-sentences = ["This is an example sentence", "Each sentence is converted"]
+sentences = ["Una ragazza si acconcia i capelli.", "Una ragazza si sta spazzolando i capelli."]
 
 model = SentenceTransformer('nickprock/stsbm-sentence-flare-it')
 embeddings = model.encode(sentences)
@@ -56,7 +56,7 @@ def mean_pooling(model_output, attention_mask):
 
 
 # Sentences we want sentence embeddings for
-sentences = ['This is an example sentence', 'Each sentence is converted']
+sentences = ["Una ragazza si acconcia i capelli.", "Una ragazza si sta spazzolando i capelli."]
 
 # Load model from HuggingFace Hub
 tokenizer = AutoTokenizer.from_pretrained('nickprock/stsbm-sentence-flare-it')