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import tensorflow as tf

model = tf.keras.Sequential([tf.keras.layers.Flatten(input_shape=(28, 28)), tf.keras.layers.Dense(64, activation='relu'), tf.keras.layers.Dropout(0.2), tf.keras.layers.Dense(128, activation='relu'), tf.keras.layers.Dropout(0.2), tf.keras.layers.Dense(128, activation='relu'), tf.keras.layers.Dropout(0.2), tf.keras.layers.Dense(10, activation='softmax')])
model.compile(metrics=['acc'], optimizer='adam', loss='sparse_categorical_crossentropy')

model.summary()