Hi @Bayram_Gulcan, This error occurs due to mismatch of model layers and weights you are trying to load. For example, if i save the model with one architecture and then try to assign those weights to another model with a different architecture then this error occurs.

```
model=keras.Sequential([
keras.Input(shape=(28,28,1)),
keras.layers.Conv2D(32,kernel_size=(3,3),activation='relu',),
keras.layers.MaxPooling2D(pool_size=(2,2)),
keras.layers.Conv2D(64,kernel_size=(3,3),activation='relu'),
keras.layers.MaxPooling2D(pool_size=(2,2)),
keras.layers.GlobalAveragePooling2D(),
keras.layers.Dropout(0.5),
keras.layers.Dense(10,activation='softmax')
])
```

If i try to assign above model weights to another model having different architecture

```
model=keras.Sequential([
keras.Input(shape=(28,28,1)),
keras.layers.Conv2D(32,kernel_size=(3,3),activation='relu',),
keras.layers.MaxPooling2D(pool_size=(2,2)),
keras.layers.Conv2D(64,kernel_size=(3,3),activation='relu'),
#maxpooling was removed here
keras.layers.GlobalAveragePooling2D(),
keras.layers.Dropout(0.5),
keras.layers.Dense(10,activation='softmax')
])
```

Then the error occurs. Thank You.