Update README.md

README.md

@@ -151,9 +151,8 @@ print(embeddings)
 import torch
 from transformers import BertModel, BertTokenizerFast
 
-
-tokenizer = BertTokenizerFast.from_pretrained("setu4993/LaBSE")
-model = BertModel.from_pretrained("setu4993/LaBSE")
+tokenizer = BertTokenizerFast.from_pretrained("sartifyllc/AviLaBSE")
+model = BertModel.from_pretrained("sartifyllc/AviLaBSE")
 model = model.eval()
 
 english_sentences = [
@@ -198,7 +197,6 @@ For similarity between sentences, an L2-norm is recommended before calculating t
 ```python
 import torch.nn.functional as F
 
-
 def similarity(embeddings_1, embeddings_2):
     normalized_embeddings_1 = F.normalize(embeddings_1, p=2)
     normalized_embeddings_2 = F.normalize(embeddings_2, p=2)