Update app.py

app.py

@@ -1,3 +1,31 @@
 import gradio as gr
+from transformers import AutoModel, AutoTokenizer
 
-gr.load("models/kakaobank/kf-deberta-base").launch()
+# Load the model and tokenizer
+model = AutoModel.from_pretrained("kakaobank/kf-deberta-base")
+tokenizer = AutoTokenizer.from_pretrained("kakaobank/kf-deberta-base")
+
+def process_text(text):
+    # Tokenize the input text
+    tokens = tokenizer.tokenize(text)
+    token_output = f"Tokens: {tokens}"
+
+    # Generate model output
+    inputs = tokenizer(text, return_tensors="pt")
+    model_output = model(**inputs)
+
+    # You might want to format this output in a more readable way
+    model_output_str = str(model_output)
+
+    return token_output, model_output_str
+
+# Create a Gradio interface
+iface = gr.Interface(
+    fn=process_text,
+    inputs=gr.inputs.Textbox(lines=2, placeholder="Enter text here..."),
+    outputs=[gr.outputs.Textbox(label="Tokenized Output"), gr.outputs.Textbox(label="Model Output")],
+    title="DeBERTa Model Text Processing",
+    description="This interface tokenizes the input text and processes it with the DeBERTa model."
+)
+
+iface.launch()