Update app.py

app.py

@@ -22,7 +22,7 @@ class RachanaLLM(nn.Module):
         return self.output_layer(output)
 
 # Load model and tokenizer
-checkpoint = torch.load("best_model.pth")  # Use your actual path
+checkpoint = torch.load("best_model.pth", map_location=torch.device('cpu'))  # Map location to CPU
 model = RachanaLLM()
 model.load_state_dict(checkpoint['model_state'] if 'model_state' in checkpoint else checkpoint)
 model.eval()