Tensorflow Fine-tuning a model from my own checkpoint
Yes, you can. After the below lines everything else will be same as what you have done previously to save the checkpoint.

with tf.Session() as sess:
  saver = tf.train.Saver()
  saver.restore(sess, tf.train.latest_checkpoint('./')) # checkpoint file path


Please refer to the below links:

https://nathanbrixius.wordpress.com/2016/05/24/checkpointing-and-reusing-tensorflow-models/

https://github.com/tensorflow/nmt/issues/51

https://blog.metaflow.fr/tensorflow-saving-restoring-and-mixing-multiple-models-c4c94d5d7125