import keras
from keras.models import Sequential
from keras.layers import Dense, Input

# Create a simple model
model = Sequential([
    Input(shape=(10,)),
    Dense(64, activation='relu', name='hidden_layer'),
    Dense(1, activation='sigmoid', name='output_layer')
])

# Compile the model
model.compile(optimizer='adam', loss='binary_crossentropy')

# Save the model
model.save('simple_model.keras')