Update README.md

README.md

@@ -8,7 +8,7 @@ tags:
 
 ---
 
-# {Ketan3101/sentensense}
+# Ketan3101/sentensense
 
 This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 768 dimensional dense vector space and can be used for tasks like clustering or semantic search.
 
@@ -28,7 +28,7 @@ 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('{Ketan3101/sentensense}')
+model = SentenceTransformer('Ketan3101/sentensense')
 embeddings = model.encode(sentences)
 # to print embeddings
 print(embeddings)
@@ -78,7 +78,7 @@ print(sentence_embeddings)
 
 <!--- 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=Ketan3101/sentensense)
+For an automated evaluation of this model, see the *Sentence Embeddings Benchmark*: [https://www.sbert.net](https://www.sbert.net/?model_name=Ketan3101/sentensense)
 
 
 ## Training