Update app.py

app.py

@@ -1,13 +1,24 @@
 import gradio as gr
 from transformers import pipeline
 
-# Load your model
-model = pipeline("fill-mask", model="Phase-Technologies/RoBERTo")
+# Load the text classification model
+model = pipeline("text-classification", model="Phase-Technologies/RoBERTo")
 
-# Define inference function
-def predict(text):
-    return model(text)
+# Define the function to classify text
+def classify_text(text):
+    result = model(text)
+    label = result[0]['label']  # Get predicted label (e.g., "POSITIVE" or "NEGATIVE")
+    confidence = round(result[0]['score'] * 100, 2)  # Get confidence score
+    return f"Prediction: {label} (Confidence: {confidence}%)"
 
-# Create Gradio UI
-iface = gr.Interface(fn=predict, inputs="text", outputs="json")
+# Create Gradio Interface
+iface = gr.Interface(
+    fn=classify_text, 
+    inputs=gr.Textbox(label="Enter Text for Sentiment Analysis"), 
+    outputs=gr.Textbox(label="Model Prediction"),
+    title="RoBERTo Sentiment Classifier",
+    description="Enter a sentence, and the model will classify it as **Positive** or **Negative**."
+)
+
+# Launch the Gradio app
 iface.launch()