Update readme

README.md

@@ -75,9 +75,9 @@ class LLMEmbeddingModel():
 
         query_instruction = "Given a search query, retrieve passages that answer the question"
         if query_instruction:
-            self.query_instruction = f"Instruction: {query_instruction} \nQuery: "
+            self.query_instruction = f"Instruction: {query_instruction} \nQuery:"
         else:
-            self.query_instruction = "Query: "
+            self.query_instruction = "Query:"
 
         self.doc_instruction = ""
         print(f"query instruction: {[self.query_instruction]}\ndoc instruction: {[self.doc_instruction]}")
@@ -210,7 +210,7 @@ embedder = HuggingFaceEmbeddings(
     model_kwargs=model_kwargs,
 )
 
-query_instruction = "Instruction: Given a search query, retrieve passages that answer the question \nQuery: "
+query_instruction = "Instruction: Given a search query, retrieve passages that answer the question \nQuery:"
 doc_instruction = ""
 
 data = [
@@ -259,7 +259,7 @@ embeddings = HuggingFaceEmbedding(
     model_name=model_name_or_path,
     trust_remote_code=True,
     device=device,
-    query_instruction="Instruction: Given a search query, retrieve passages that answer the question \nQuery: ",  
+    query_instruction="Instruction: Given a search query, retrieve passages that answer the question \nQuery:",  
     text_instruction=""
 )