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README.md

@@ -5,9 +5,10 @@ tags:
 - feature-extraction
 - sentence-similarity
 - transformers
+lan: ko
 ---
 
-# {MODEL_NAME}
+# TAACO_Similarity
 
 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.
 
@@ -34,8 +35,9 @@ print(embeddings)
 
 
 
-## Usage (HuggingFace Transformers)
-Without [sentence-transformers](https://www.SBERT.net), you can use the model like this: First, you pass your input through the transformer model, then you have to apply the right pooling-operation on-top of the contextualized word embeddings.
+## Usage (실제 문장 간 유사도 비교)
+Sentence-transformers [sentence-transformers](https://www.SBERT.net) 를 설치한 후 아래 내용과 같이 문장 간 유사도를 비교할 수 있습니다.
+query 변수는 비교 기준이 되는 문장(Source Sentence)이고 비교를 진행할 문장은 docs에 list 형식으로 구성하시면 됩니다.
 
 ```python
 model = SentenceTransformer("KDHyun08/TAACO_STS")