Update app.py

app.py

@@ -1,3 +1,25 @@
 import gradio as gr
+from transformers import TextClassificationPipeline, AutoTokenizer, AutoModelForSequenceClassification
 
-gr.Interface.load("models/KoalaAI/Text-Moderation").launch()
+# Load a pre-trained text classification model 
+model_name = "KoalaAI/Text-Moderation" 
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForSequenceClassification.from_pretrained(model_name)
+
+# Create a TextClassificationPipeline
+pipe = TextClassificationPipeline(model=model, tokenizer=tokenizer)
+
+# Define the classify_text function using the pipeline
+def classify_text(text):
+    prediction = pipe(text)[0]["label"]
+    return prediction
+
+# Create a Gradio interface
+iface = gr.Interface(
+    fn=classify_text,
+    inputs=gr.inputs.Textbox(label="Enter text"),
+    outputs=gr.outputs.Label(label="Predicted classes"),
+)
+
+# Launch the Gradio app
+iface.launch()