Update app.py

app.py

@@ -4,7 +4,7 @@ import torch
 from transformers import (
     Wav2Vec2ForCTC, Wav2Vec2Processor, 
     MarianMTModel, MarianTokenizer, 
-    BertForSequenceClassification, AutoModel, AutoTokenizer
+    BertForSequenceClassification, AutoModel, AutoTokenizer,AutoModelForSequenceClassification
 )
 
 # Detect device
@@ -35,7 +35,7 @@ bert_model = BertForSequenceClassification.from_pretrained(bert_model_name, num_
 # Charger le modèle et le tokenizer Darija
 sentiment_model_name = "BenhamdaneNawfal/sentiment-analysis-darija"
 sentiment_tokenizer = AutoTokenizer.from_pretrained(sentiment_model_name)
-sentiment_model = AutoModelForSequenceClassification.from_pretrained(sentiment_model_name).to("cuda" if torch.cuda.is_available() else "cpu")
+sentiment_model = AutoModelForSequenceClassification.from_pretrained(sentiment_model_name,num_labels=3).to("cuda" if torch.cuda.is_available() else "cpu")
 
 # Labels du modèle (à modifier selon le modèle utilisé)
 sentiment_labels = ["Négatif", "Neutre", "Positif"]