Update README.md

README.md

@@ -26,7 +26,7 @@ query = "How many people live in London?"
 docs = ["Around 9 Million people live in London", "London is known for its financial district"]
 
 #Load the model
-model = SentenceTransformer('sentence-transformers/msmarco-distilbert-dot-v4')
+model = SentenceTransformer('sentence-transformers/msmarco-distilbert-dot-v5')
 
 #Encode query and documents
 query_emb = model.encode(query)
@@ -82,8 +82,8 @@ query = "How many people live in London?"
 docs = ["Around 9 Million people live in London", "London is known for its financial district"]
 
 # Load model from HuggingFace Hub
-tokenizer = AutoTokenizer.from_pretrained("sentence-transformers/msmarco-distilbert-dot-v4")
-model = AutoModel.from_pretrained("sentence-transformers/msmarco-distilbert-dot-v4")
+tokenizer = AutoTokenizer.from_pretrained("sentence-transformers/msmarco-distilbert-dot-v5")
+model = AutoModel.from_pretrained("sentence-transformers/msmarco-distilbert-dot-v5")
 
 #Encode query and docs
 query_emb = encode(query)
@@ -121,7 +121,7 @@ In the following some technical details how this model must be used:
 
 <!--- Describe how your model was evaluated -->
 
-For an automated evaluation of this model, see the *Sentence Embeddings Benchmark*: [https://seb.sbert.net](https://seb.sbert.net?model_name=msmarco-distilbert-base-dot-v4)
+For an automated evaluation of this model, see the *Sentence Embeddings Benchmark*: [https://seb.sbert.net](https://seb.sbert.net?model_name=msmarco-distilbert-base-dot-v5)
 
 
 ## Training