Update README.md

Fixed model path in the example.

README.md

@@ -31,7 +31,7 @@ Then you can use the model like this:
 from sentence_transformers import SentenceTransformer
 sentences = ["Ala ma kota", "Ala ma psa"]
 
-model = SentenceTransformer('polish-roberta-large-v2-sts')
+model = SentenceTransformer('radlab/polish-roberta-large-v2-sts')
 embeddings = model.encode(sentences)
 print(embeddings)
 ```
@@ -57,8 +57,8 @@ def mean_pooling(model_output, attention_mask):
 sentences = ['Ala ma kota', 'Ala ma psa']
 
 # Load model from HuggingFace Hub
-tokenizer = AutoTokenizer.from_pretrained('polish-roberta-large-v2-sts')
-model = AutoModel.from_pretrained('polish-roberta-large-v2-sts')
+tokenizer = AutoTokenizer.from_pretrained('radlab/polish-roberta-large-v2-sts')
+model = AutoModel.from_pretrained('radlab/polish-roberta-large-v2-sts')
 
 # Tokenize sentences
 encoded_input = tokenizer(sentences, padding=True, truncation=True, return_tensors='pt')