Update app.py

app.py

@@ -1,11 +1,10 @@
 #gr.Interface.load("models/hipnologo/gpt2-imdb-finetune").launch()
 import gradio as gr
-from gradio import Interface
 from transformers import AutoTokenizer, AutoModelForSequenceClassification
 
 def predict_review(text):
     # Specify the model name or path
-    model_name = "hipnologo/gpt2-imdb-finetune"  # Replace with your model name on the Hugging Face model hub
+    model_name = "hipnologo/gpt2-imdb-finetune"  
 
     # Load your model and tokenizer
     tokenizer = AutoTokenizer.from_pretrained(model_name)
@@ -27,12 +26,11 @@ def predict_review(text):
     result_md = f"Sentiment: {sentiment}"
     return result_md
 
-iface = Interface(
+iface = gr.Interface(
     fn=predict_review, 
-    inputs=gr.inputs.Textbox(lines=7, placeholder="Enter text here..."), 
-    outputs=gr.outputs.Textbox(),
+    inputs=gr.components.Textbox(lines=7, placeholder="Enter text here..."), 
+    outputs=gr.components.Textbox(),
     title="Sentiment Analysis",
-    description="This application predicts the sentiment (Positive/Negative) of the input text using a fine-tuned GPT-2 model.",
-    theme="compact"  # change this to the theme you prefer: 'huggingface', 'default'
+    description="This application predicts the sentiment (Positive/Negative) of the input text using a fine-tuned GPT-2 model."
 )
 iface.launch()