Update README.md

README.md

@@ -19,7 +19,7 @@ datasets:
 - embedding-data/WikiAnswers
 ---
 
-# multi-qa-MiniLM-L6-cos-v1
+# Multilingual-Text-Semantic-Search-Siamese-BERT
 This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 384 dimensional dense vector space and was designed for **semantic search**. It has been trained on 215M (question, answer) pairs from diverse sources. For an introduction to semantic search, have a look at: [SBERT.net - Semantic Search](https://www.sbert.net/examples/applications/semantic-search/README.html)
 
 
@@ -38,7 +38,7 @@ 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/multi-qa-MiniLM-L6-cos-v1')
+model = SentenceTransformer('SeyedAli/Multilingual-Text-Semantic-Search-Siamese-BERT-V1')
 
 #Encode query and documents
 query_emb = model.encode(query)