Tensorflow: How to initialize embeddings layer within Estimator API?

I'm trying to use existing embeddings within tensorflow model, the size of embedding is greater than 2Gb and this makes my original try of doing this unsuccessful:

embedding_var = tf.get_variable(
        "embeddings", 
        shape=GLOVE_MATRIX.shape, 
        initializer=tf.constant_initializer(np.array(GLOVE_MATRIX))
)

Which gave me this error:

Cannot create a tensor proto whose content is larger than 2GB.

I'm using AWS SageMaker, which based on the Estimator API, and the actual running of the graph in session happens behind the scene, so I'm not sure how to initialize some placeholders for embedding given that. Would be helpful if someone will be able to share the way how to do such initialization in term of EstimatorAPI.

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