Update services/sentiment.py

services/sentiment.py

@@ -1,9 +1,8 @@
 from transformers import pipeline
 
-# 🔥 lebih ringan daripada load manual
 classifier = pipeline(
     "sentiment-analysis",
-    model="indobenchmark/indobert-base-p1"
+    model="w11wo/indonesian-roberta-base-sentiment-classifier"
 )
 
 def predict(texts):
@@ -12,13 +11,15 @@ def predict(texts):
     try:
         outputs = classifier(texts)
         for o in outputs:
-            label = o['label']
-            if label == 'LABEL_0':
+            label = o['label'].lower()
+
+            if "positive" in label:
+                results.append("Positive")
+            elif "negative" in label:
                 results.append("Negative")
-            elif label == 'LABEL_1':
-                results.append("Neutral")
             else:
-                results.append("Positive")
+                results.append("Neutral")
+
     except:
         results = ["Neutral"] * len(texts)