quantize_model() cannot detect a keras.Sequential model

Prior to filing: check that this should be a bug instead of a feature request. Everything supported, including the compatible versions of TensorFlow, is listed in the overview page of each technique. For example, the overview page of quantization-aware training is here. An issue for anything not supported should be a feature request.

Describe the bug
I'm passing a keras sequential model into quantize_model(), and I'm getting the error that the model isn't a sequential model.

System information

Carried out in:
Google Colab

TensorFlow version (installed from source or binary):
2.17.0

TensorFlow Model Optimization version (installed from source or binary):
0.8.0

Python version:
3.10.12

Describe the expected behavior
prepare a keras sequential model built from scratch that was imported via load_model()

Describe the current behavior
ValueError: to_quantize can only either be a keras Sequential or Functional model.

Code to reproduce the issue
!pip install tensorflow_model_optimization

import pandas as pd
import numpy as np
import time
import tensorflow as tf
import os
import tempfile
import keras
import tensorflow_model_optimization as tfmot
from google.colab import drive
from tensorflow.keras.models import load_model

drive.mount('/content/drive')
%cd /content/drive/My Drive/CS528/HW3

model = load_model('/content/drive/My Drive/CS528/HW3/q1_model.keras')

quant_aware_model_tflite = '/content/drive/My Drive/CS528/HW3/s_mnist_quant_aware_training.tflite'
quantize_model = tfmot.quantization.keras.quantize_model
q_aware_model = quantize_model(model)

Screenshots
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Additional context
I've already checked the same compound conditional using the imported model just before calling quantize_model(), and it behaves as it should. Only when quantize_model() is actually handling the model does it seem to think the model isn't a tf.keras.Sequential object.

Start by reproducing the reported failure with TensorFlow 2.17.0, TensorFlow Model Optimization 0.8.0, and the loaded model from load_model(). Read the quantize_model() entry point and its Sequential or Functional model check. Done means a keras.Sequential model loaded from a .keras file is accepted, with regression coverage for the reported case.