Update README.md

README.md

@@ -6,8 +6,9 @@ tags:
 - sentence-similarity
 ---
 
-# {klue-sbert-128d-v1}
-
+# klue-sbert-128d-v1
+- 기존 klue 모델을, 128 차원으로 축소하는 dense 추가하여 nli(3)-sts(10) 훈련 시킨 모델.
+  
 This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 128 dimensional dense vector space and can be used for tasks like clustering or semantic search.
 
 <!--- Describe your model here -->
@@ -26,7 +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('klue-sbert-128d-v1')
+model = SentenceTransformer('bongsoo/klue-sbert-128d-v1')
 embeddings = model.encode(sentences)
 print(embeddings)
 ```