Drawing CNN architecture in LeNet style

I want to draw my CNN model in LeNet style. I found online simulator http://alexlenail.me/NN-SVG/LeNet.html but I don't know how to use it with my model. I want to fill the site with my model parameters but I don't know the parameters I should write in each step in the site.

Any help would be appreciated. I have tried many times to draw my model in LeNet style but I can't do it.

Model:

    input_shape=(33,3840,1)
    model = Sequential()
    #C1
    model.add(Conv2D(16, (5, 5), strides=( 2, 2), padding='same',activation='relu', input_shape=input_shape))
    model.add(keras.layers.MaxPooling2D(pool_size=( 2, 2),  padding='same'))
    model.add(BatchNormalization())

    #C2
    model.add(Conv2D(32, ( 3, 3), strides=(1,1), padding='same',  activation='relu'))
    model.add(keras.layers.MaxPooling2D(pool_size=(2, 2), padding='same'))
    model.add(BatchNormalization())
     
    model.add(Dense(32, input_dim=32,kernel_regularizer=regularizers.l2(0.1)))
    model.add(keras.layers.Dropout(0.6))

    
    model.add(Flatten())
    model.add(Dropout(0.6))
    model.add(Dense(256, activation='sigmoid'))
    model.add(Dropout(0.6))
    model.add(Dense(2, activation='softmax'))

    opt_adam = keras.optimizers.Adam(lr=0.0001, beta_1=0.9, beta_2=0.999, epsilon=1e-08, decay=0.0)
    model.compile(loss=categorical_focal_loss(), optimizer=opt_adam, metrics=['accuracy'])