Update README.md

README.md

@@ -34,7 +34,7 @@ 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 = ["De kat slaapt op het bed.", "De poes rust op het matras."]
 
 model = SentenceTransformer('textgain/allnli-GroNLP-bert-base-dutch-cased')
 embeddings = model.encode(sentences)
@@ -59,7 +59,7 @@ def mean_pooling(model_output, attention_mask):
 
 
 # Sentences we want sentence embeddings for
-sentences = ['This is an example sentence', 'Each sentence is converted']
+sentences = ["De kat slaapt op het bed.", "De poes rust op het matras."]
 
 # Load model from HuggingFace Hub
 tokenizer = AutoTokenizer.from_pretrained('textgain/allnli-GroNLP-bert-base-dutch-cased')