Update app.py

app.py

@@ -1,6 +1,6 @@
 import gradio as gr
 # BE EXPLICIT: Import the specific model class we need
-from transformers import AutoTokenizer, XLMRobertaForSequenceClassification
+from transformers import AutoTokenizer, AutoModelForSequenceClassification
 import torch
 import os
 
@@ -23,7 +23,8 @@ try:
     # THE FIX: Use the explicit class instead of AutoModelForSequenceClassification.
     # This ignores the problematic 'auto_map' in config.json and forces the
     # use of the standard XLM-RoBERTa architecture for sequence classification.
-    model = XLMRobertaForSequenceClassification.from_pretrained(MODEL_ID, token=HF_TOKEN, trust_remote_code=True)
+    model = AutoModelForSequenceClassification.from_pretrained("Lajavaness/bilingual-embedding-base", token=HF_TOKEN, trust_remote_code=True)
+    model = AutoModelForSequenceClassification.from_pretrained(MODEL_ID, token=HF_TOKEN, trust_remote_code=True)
     
     # Move the model to the selected device
     model.to(device)