Update app.py

app.py

@@ -1,11 +1,23 @@
 import gradio as gr
 from transformers import pipeline
 
-nlp = pipeline('text-generation')
+nlp = pipeline("text-classification")
 
-def generate_text(prompt):
-  response = nlp(prompt, max_length=100, num_return_sequences=1)[0]
-  return response['generated_text']
+def classify_text(input_text):
+    result = nlp(input_text)[0]
+    return result["label"], result["score"]
 
-iface = gr.Interface(generate_text, gr.inputs.Textbox(), gr.outputs.Textbox())
-iface.launch()
+with gr.Blocks() as demo:
+    with gr.Row():
+        with gr.Column():
+            text_input = gr.Textbox(label="Enter text to classify")
+            classify_btn = gr.Button(value="Classify")
+        with gr.Column():
+            label_output = gr.Textbox(label="Predicted label")
+            score_output = gr.Textbox(label="Score")
+
+    classify_btn.click(classify_text, inputs=text_input, outputs=[label_output, score_output], api_name="classify-text")
+    examples = gr.Examples(examples=["This is a positive review.", "This is a negative review."],
+                           inputs=[text_input])
+
+demo.launch()