Update app.py

app.py

@@ -8,8 +8,8 @@ import torch
 tokenizer = T5Tokenizer.from_pretrained("UBC-NLP/araT5-base")
 model = T5ForConditionalGeneration.from_pretrained("UBC-NLP/araT5-base")
 
-# Emotion classification pipeline for Arabic (use an Arabic emotion classification model)
-emotion_classifier = pipeline("text-classification", model="d0r13n/ara-bert-base-arabic-emotion")
+# Emotion classification pipeline (updated model for Arabic emotion classification)
+emotion_classifier = pipeline("text-classification", model="aubmindlab/bert-base-arabertv2")
 
 # Function to get embeddings from ARAT5 for topic modeling
 def generate_embeddings(texts):