Update README.md

README.md

@@ -24,8 +24,15 @@ model.eval()
 query_prefix = 'Represent this sentence for searching relevant passages: '
 
 # Your queries and docs.
-queries  = ['what is snowflake?', 'Where can I get the best tacos?']
-documents = ['The Data Cloud!', 'Mexico City of Course!']
+queries = [
+    "What is vector search?",
+    "Where can I get the best pizza?"
+]
+
+documents = [
+    "Marqo is an end-to-end platform for embedding training and retrieval.",
+    "Definitely Naples! The birthplace of pizza, and it’s as authentic as it gets."
+]
 
 
 # Add query prefix and tokenize queries and docs.
@@ -54,12 +61,12 @@ for query, query_scores in zip(queries, scores):
         print(f'Score: {score:.4f} | Document: "{document}"')
     print()
 
-#### OUTPUT ####
-# Query: "what is snowflake?"
-# Score: 0.3025 | Document: "The Data Cloud!"
-# Score: 0.2297 | Document: "Mexico City of Course!"
 
-# Query: "Where can I get the best tacos?"
-# Score: 0.4512 | Document: "Mexico City of Course!"
-# Score: 0.2336 | Document: "The Data Cloud!"
+# Query: "What is vector search?"
+# Score: 0.4194 | Document: "Marqo is an end-to-end platform for embedding training and retrieval."
+# Score: 0.1853 | Document: "Definitely Naples! The birthplace of pizza, and it’s as authentic as it gets."
+
+# Query: "Where can I get the best pizza?"
+# Score: 0.6144 | Document: "Definitely Naples! The birthplace of pizza, and it’s as authentic as it gets."
+# Score: 0.2787 | Document: "Marqo is an end-to-end platform for embedding training and retrieval."
 ```