'update load'

app.py

@@ -36,10 +36,12 @@ class LSTMModel(nn.Module):
 # loading model from checkpoint
 model = LSTMModel(VOCAB_SIZE, EMBEDDING_DIM, N_UNITS).to(device)
 
+device = 'cpu'
 
 checkpoint_path = 'recipe_generator_LSTM.pth'
-checkpoint = torch.load(checkpoint_path)
-model.load_state_dict(checkpoint['model_state_dict'])
+checkpoint = torch.load(checkpoint_path, map_location=device)
+model.load_state_dict(checkpoint)
+
 print('Loaded model from checkpoint')
 
 def load_vocab(directory):