Update README.md

README.md

@@ -38,10 +38,7 @@ def get_score(model, tokenizer, prompt, response):
     # Extract the logits
     logits = outputs.logits
 
-    # Calculate the score as the maximum logit value
-    score = torch.max(logits).item()
-
-    return score
+    return logits.item()
 
 # Example usage
 prompt = "What is Depreciation"
@@ -50,11 +47,11 @@ example_preferred_response = "Depreciation is the drop in value of an asset due
 
 score = get_score(model, tokenizer, prompt, example_less_pref_response)
 print(score)
-# >> -9.01173
+# >> -3.915163993835449
 
 score = get_score(model, tokenizer, prompt, example_preferred_response)
 print(score)
-# >> 1.976404
+# >> 7.460323333740234
 ```
 
 ## Scored examples