Update README.md

README.md

@@ -6,7 +6,7 @@ tags:
 - sentence-similarity
 ---
 
-# {MODEL_NAME}
+# LazarusNLP/congen-indobert-base
 
 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.
 
@@ -26,7 +26,7 @@ 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('LazarusNLP/congen-indobert-base')
 embeddings = model.encode(sentences)
 print(embeddings)
 ```
@@ -37,7 +37,7 @@ print(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={MODEL_NAME})
+For an automated evaluation of this model, see the *Sentence Embeddings Benchmark*: [https://seb.sbert.net](https://seb.sbert.net?model_name=LazarusNLP/congen-indobert-base)
 
 
 ## Training