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Keras model for classification with multiple classes

I am trying to use a keras model for classification. So far I have figured out how to do it with one class. But I would like to classify multiple classes.
model = Sequential([
Dense(100, input_dim=8, activation=’relu’),
Dense(1, activation=’softmax’)
])
model.compile(loss=’categorical_crossentropy’, optimizer=’adam’, metrics=[‘accuracy’])

y_train = np.array(y_train)
y_test = np.array(y_test)

x_train = model.predict(np.array(x_train), batch_size=32)
x_test = model.predict(np.array(x_test), batch_size=32)

I tried to use the following:
y_train = np.array(y_train)
y_test = np.array(y_test)

x_train = model.predict(np.array(x_train), batch_size=32)
x_test = model.predict(np.array(x_test), batch_size=32)

However, it yields:
ValueError: Error when checking target: expected dense_2 to have shape (None,) but got array with shape (2,)

I have also tried with the following:
x_train = np.reshape(x_train, (x_train.shape[0], x_train.shape[1], 1))
x_test = np.reshape(x_test, (x_test.shape[0], x_test.shape[1], 1))

However it yields:
ValueError: Shapes must be equal, but are 8 and 7 for ‘dense_1/bias_add’

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