update README.md

README.md

@@ -33,7 +33,7 @@ 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 = ["Bu örnek bir cümle", "Her cümle dönüştürülür"]
 
 model = SentenceTransformer('atasoglu/turkish-mini-bert-uncased-mean-nli-stsb-tr')
 embeddings = model.encode(sentences)
@@ -58,7 +58,7 @@ def mean_pooling(model_output, attention_mask):
 
 
 # Sentences we want sentence embeddings for
-sentences = ['This is an example sentence', 'Each sentence is converted']
+sentences = ["Bu örnek bir cümle", "Her cümle dönüştürülür"]
 
 # Load model from HuggingFace Hub
 tokenizer = AutoTokenizer.from_pretrained('atasoglu/turkish-mini-bert-uncased-mean-nli-stsb-tr')