load_model error: ValueError: Improperly formatted model config when tensorflow.keras - tensorflow

Question

I can load the model with load_model("model.h5") in colab and do a model.predict which works. But when I download the h5 file and run load_model locally, the load_model call gets an error "ValueError: Improperly formatted model config."
This is the model:
base_model=MobileNet(weights='imagenet',include_top=False) #imports the mobilenet model and discards the last 1000 neuron layer.
x=base_model.output
x=GlobalAveragePooling2D()(x)
x=Dense(1024,activation='relu')(x) #we add dense layers so that the model can learn more complex functions and classify for better results.
x=Dense(1024,activation='relu')(x) #dense layer 2
x=Dense(512,activation='relu')(x) #dense layer 3
preds=Dense(2,activation='softmax')(x) #final layer with softmax activation
using transfer learning
model=Model(inputs=base_model.input,outputs=preds)
for layer in model.layers[:20]:
layer.trainable=False
for layer in model.layers[20:]:
layer.trainable=True
then trained
train_generator=train_datagen.flow_from_directory('/content/chest_xray/train/',
target_size=(224,224),
color_mode='rgb',
batch_size=32,
class_mode='categorical', shuffle=True)
model.compile(optimizer='Adam',loss='categorical_crossentropy',metrics=['accuracy'])
# Adam optimizer
# loss function will be categorical cross entropy
# evaluation metric will be accuracy
step_size_train=train_generator.n//train_generator.batch_size
model.fit_generator(generator=train_generator,
steps_per_epoch=step_size_train,
epochs=5)
model saved
model.save('chest-xray-pneumonia.h5')
prediction works
ill_path = "/content/chest_xray/train/PNEUMONIA/"
good_path = "/content/chest_xray/train/NORMAL/"
ill_pic = ill_path + os.listdir(ill_path)[1]
good_pic = good_path + os.listdir(good_path)[1]
print(get_rez(ill_pic))
print(get_rez(good_pic))
But locally running in a Flask app python script main.py, it doesn't
from flask import render_template, jsonify, Flask, redirect, url_for, request
from app import app
import random
import os
from tensorflow.keras.applications.resnet50 import ResNet50
from tensorflow.keras.models import load_model
from tensorflow.keras.preprocessing import image
from tensorflow.keras.applications.mobilenet import preprocess_input, decode_predictions
import numpy as np
import ipdb
weightsPath = app.config['UPLOAD_FOLDER']
get error on the next line: ValueError: Improperly formatted model config.
new_model = load_model(os.path.join(app.config['UPLOAD_FOLDER'],"chest-xray-pneumonia.h5"))
def upload_file():
if request.method == 'POST':
f = request.files['file']
path = os.path.join(app.config['UPLOAD_FOLDER'], f.filename)
#f.save(os.path.join(app.config['UPLOAD_FOLDER'], f.filename))
ill_pic = os.path.join(app.config['UPLOAD_FOLDER'],
f.filename)
print(get_rez(ill_pic))