Update app.py

app.py

@@ -91,8 +91,8 @@ def analyze(text):
 
     # Load the tokenizer and model
     tokenizer = load_tokenizer(model_card)
-    sentiment_model = load_model(sentiment_model)
-    subjectivity_model = load_model(subjectivity_only_model)
+    model_with_sentiment = load_model(sentiment_model)
+    model_without_sentiment = load_model(subjectivity_only_model)
 
     # Tokenize
     inputs = tokenizer(text, padding=True, truncation=True, max_length=256, return_tensors='pt')
@@ -107,14 +107,14 @@ def analyze(text):
     inputs['negative'] = torch.tensor(negative).unsqueeze(0)
 
     # Get the sentiment model outputs
-    outputs1 = sentiment_model(**inputs)
+    outputs1 = model_with_sentiment(**inputs)
     logits1 = outputs1.get('logits')
 
     # Calculate probabilities using softmax
     p1 = torch.nn.functional.softmax(logits1, dim=1)[0]
 
     # Get the subjectivity model outputs
-    outputs2 = subjectivity_model(**inputs)
+    outputs2 = model_without_sentiment(**inputs)
     logits2 = outputs2.get('logits')
     # Calculate probabilities using softmax
     p2 = torch.nn.functional.softmax(logits2, dim=1)[0]