input: Write a python function to create a Sequential model with Keras having specific layers and compile settings.
  assert create_sequential_model().layers[0].input_shape == (None, 6)
  assert create_sequential_model().layers[0].units == 8
  assert create_sequential_model().layers[1].units == 4
  assert create_sequential_model().loss == 'categorical_crossentropy'
  assert create_sequential_model().optimizer.get_config()['name'] == 'Adam'
  assert 'accuracy' in create_sequential_model().metrics_names
output: def create_sequential_model():
      from tensorflow.keras.models import Sequential
      from tensorflow.keras.layers import Dense
      from tensorflow.keras.optimizers import Adam
      
      model = Sequential()
      model.add(Dense(8, input_shape=(6,), activation='relu'))
      model.add(Dense(4, activation='softmax'))
      
      model.compile(optimizer=Adam(), loss='categorical_crossentropy', metrics=['accuracy'])
      
      return model