Update README.md

README.md

@@ -7,9 +7,7 @@ tags:
 license: mit
 ---
 
-[MODEL_NAME]: "smart-tribune/sentence-transformers-multilingual-e5-large"
-
-# {MODEL_NAME}
+# smart-tribune/sentence-transformers-multilingual-e5-large
 
 This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 1024 dimensional dense vector space and can be used for tasks like clustering or semantic search.
 
@@ -29,7 +27,7 @@ Then you can use the model like this:
 from sentence_transformers import SentenceTransformer
 sentences = ["This is an example sentence", "Each sentence is converted"]
 
-model = SentenceTransformer('{MODEL_NAME}')
+model = SentenceTransformer('smart-tribune/sentence-transformers-multilingual-e5-large')
 embeddings = model.encode(sentences)
 print(embeddings)
 ```