Update README.md

README.md

@@ -32,7 +32,7 @@ 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/sentence-bert-base-italian-xxl-cased')
 embeddings = model.encode(sentences)
@@ -57,7 +57,7 @@ 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/sentence-bert-base-italian-xxl-cased')