Update app.py

app.py

@@ -1,8 +1,18 @@
 import gradio as gr
+from transformers import AutoModel
+import torch
+
+# Load the model
+model = AutoModel.from_pretrained("huggingface/autoformer-tourism-monthly")
 
 def forecast(month: str):
-    # Dummy output for now (we’ll replace with real model later)
-    return f"Predicted tourism for {month}: 1.2M visitors"
+    # Simulated input tensor — replace with real preprocessing if available
+    dummy_input = torch.rand(1, 36, 1)  # e.g. 36 months of past data
+    output = model(dummy_input)
+
+    # Simulate response (actual model output may vary depending on structure)
+    prediction = output.last_hidden_state.mean().item()
+    return f"Predicted tourism for {month}: {round(prediction * 1_000_000, 2)} visitors"
 
 gr.Interface(
     fn=forecast,