Update app.py

app.py

@@ -4,8 +4,10 @@ import pandas as pd
 import numpy as np
 
 # Carregar o modelo
-model = TimeSeriesTransformerForPrediction.from_pretrained("google/timesfm-2.0-500m-pytorch")
-
+model = TimeSeriesTransformerForPrediction.from_pretrained(
+    "google/timesfm-2.0-500m-pytorch",
+    torch_dtype="auto"  # Garante compatibilidade
+)
 def prever_vendas(historico):
     # Converter entrada em lista de números
     historico = [float(x) for x in historico.split(",")]