Update app.py

app.py

@@ -1,20 +1,15 @@
 import gradio as gr
+from transformers import pipeline
 
-def predict_sentiment(text):
-    model_output = gr.load("models/quocviethere/roberta-sentiment-model").process(text)
-    # Convert the model output to a more readable format
-    if model_output[0] > model_output[1]:  # Assuming index 0 is for negative sentiment
-        return "Negative Review", model_output[0]
-    else:
-        return "Positive Review", model_output[1]
+sentiment = pipeline("sentiment-analysis")
 
-iface = gr.Interface(
-    fn=predict_sentiment, 
-    inputs=gr.Textbox(lines=2, placeholder="Type your review here"),  # define the text input
-    outputs=gr.Label(num_top_classes=2)  # define the output as a label
-)
-
-# Launch the interface
-iface.launch()
+def get_sentiment(input_text):
+    return sentiment(input_text)
 
+iface = gr.Interface(fn = get_sentiment,
+                     inputs = "text",
+                     outputs = ['text'],
+                     title='Sentiment Analysis',
+                     description = "get sentiment")
 
+iface.launch(inline = False)