Load model tensorflow

from tensorflow import keras
model = keras.models.load_model('path/to/location')

Load saved model tensorflow

new_model = tf.keras.models.load_model('my_model.h5')

Source: tensorflow.org

Use model from checkpoint tensorflow

 
with tf.Session() as sess:
  new_saver = tf.train.import_meta_graph('my_test_model-1000.meta')
  new_saver.restore(sess, tf.train.latest_checkpoint('./'))

Source: cv-tricks.com

Use model from checkpoint tensorflow

 
with tf.Session() as sess:    
    saver = tf.train.import_meta_graph('my-model-1000.meta')
    saver.restore(sess,tf.train.latest_checkpoint('./'))
    print(sess.run('w1:0'))
##Model has been restored. Above statement will print the saved value of w1.

Source: cv-tricks.com

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