Update app.py

app.py

@@ -1,6 +1,6 @@
 import gradio as gr
 import torch
-from transformers import BertTokenizer, BertModel  
+from transformers import BertTokenizer
 import torch.nn.functional as F
 
 # Load model and tokenizer from Hugging Face
@@ -25,12 +25,13 @@ class IndoBERTMultiTaskClassifier(torch.nn.Module):
 
         return logits_task1, logits_task2
 
-# Load model directly from Hugging Face
+# Load the model checkpoint into your multitask model class
 model = IndoBERTMultiTaskClassifier(
     bert_model_name=model_name,
     num_labels_task1=3,  # Adjust with your task1 classes
     num_labels_task2=3   # Adjust with your task2 classes
 )
+model.load_state_dict(torch.load("pytorch_model.bin", map_location=torch.device('cpu')))
 model.eval()
 
 # Define label mappings
@@ -62,8 +63,8 @@ iface = gr.Interface(
     fn=classify, 
     inputs="text", 
     outputs=[
-        gr.outputs.Label(label="Fake Review Detection"), 
-        gr.outputs.Label(label="Sentiment Classification")
+        gr.Label(label="Fake Review Detection"), 
+        gr.Label(label="Sentiment Classification")
     ],
     title="Multitask IndoBERT: Fake Review & Sentiment Classification",
     description="Enter a skincare product review in Indonesian and the model will classify it as fake or trusted, and determine the sentiment.",