updates Readme

README.md

@@ -69,20 +69,15 @@ sim = model.similarity(query_embed, document_embed)
 print(f"Similarity: {sim}")
 # Similarity: tensor([[22.3299]])
 
-# Visualize top tokens for each text
-top_k = 8
-print(f"\nTop tokens {top_k} for each text:")
-
-decoded_query = model.decode(query_embed, top_k=top_k)
+decoded_query = model.decode(query_embed)
 decoded_document = model.decode(document_embed)
 
-for i in range(top_k):
+for i in range(len(decoded_query)):
     query_token, query_score = decoded_query[i]
     doc_score = next((score for token, score in decoded_document if token == query_token), 0)
     if doc_score != 0:
         print(f"Token: {query_token}, Query score: {query_score:.4f}, Document score: {doc_score:.4f}")
 
-# Top tokens 30 for each text:
 # Token: ny, Query score: 2.9262, Document score: 2.1335
 # Token: weather, Query score: 2.5206, Document score: 1.5277
 # Token: york, Query score: 2.0373, Document score: 2.3489