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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):
# 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,
inputs=gr.Textbox(label="Enter Month (e.g. Jan 2023)"),
outputs=gr.Textbox(label="Tourism Forecast"),
title="AI Tourism Predictor",
description="Predict future tourism stats using Autoformer model."
).launch()
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