When you acess layers of the trained model by name, do you also get the weights?

Quick question, so, i’ve got some model (an autoencoder to be
exact) written in a sequential manner and let’s say it looks
something like this

input = keras.Input() conv = layers.Conv2D()(input) flatten = layers.Flatten()(conv) dense = layers.Dense()(flatten) out = layers.Dense()(dense) model = keras.Model(inputs=input, outputs=out) model.compile() 

and let’s say i’ve trained that model. If i then use some layers
of that model to make another one like this

new_model = keras.Model(inputs=input, outputs=conv) 

will that new model be already trained? I guess it poses more
global question, does keras.Model() create separate object which
uses those layers vairables you’ve written just to know the
structure, like a Class description or does it actually acts upon
those variables during actions like .fit()?