Update app.py

app.py

@@ -1,3 +1,22 @@
 import gradio as gr
 
-gr.load("models/cerebras/btlm-3b-8k-chat").launch()
+# Optional: Define a wrapper function for your model
+def model_wrapper(text):
+    try:
+        # Load the model with custom code execution allowed
+        model = gr.load("models/cerebras/btlm-3b-8k-chat", trust_remote_code=True)
+        # Use the model to predict
+        return model(text)
+    except Exception as e:
+        # Log the exception or handle it in a user-friendly way
+        return f"An error occurred: {str(e)}"
+
+# Setup Gradio interface
+iface = gr.Interface(
+    fn=model_wrapper,  # your function to expose
+    inputs="text",  # input type
+    outputs="text"  # output type
+)
+
+# Launch the Gradio app
+iface.launch()