Update app.py

app.py

@@ -1,3 +1,24 @@
 import gradio as gr
+from transformers import pipeline
 
-gr.Interface.load("models/kelvinleong/KT_Roberta-Base_Class").launch()
+# Load text classification model from Hugging Face
+model = pipeline("text-classification", model="distilbert-base-uncased-finetuned-sst-2-english")
+
+def classify_text(text):
+    # Classify text using the loaded model
+    result = model(text)[0]
+    label = result['label']
+    score = result['score']
+    return f"Label: {label}, Score: {score}"
+
+# Create Gradio interface
+iface = gr.Interface(
+    fn=classify_text,
+    inputs=gr.inputs.Textbox(label="Enter text to classify"),
+    outputs="text",
+    title="Text Classification with Hugging Face",
+    description="Classify text using a pre-trained model from Hugging Face."
+)
+
+# Launch the interface
+iface.launch()