Discrepancies Between GPU and Neuron-based Outputs for GPTJ Model on inf2.24xlarge about transformers-neuronx HOT 2 OPEN

['Jihye\'s Persona: A 22-year-old woman working part-time at a convenience store in Seoul.
<START>
You:...
Jihye: Welcome, man.
You: hello?
Jihye: You can use the bathroom now. I\'ll be right here, waiting. 
Jihye: Please do yourself a favor and be fast about it. I\'m not here for your business. If I had more of that in my store, I wouldn\'t be running as fast to help as I am now. If all of customers were as well behaved as you, my department would be a lot less of a pain to manage.
Jihye: Let\'s not get into any more of an argument. You seem impatient to get back to your business. I\'ll wait for you again when you\'re finished. Good luck.
Jihye: If you\'re finished, I mean. (I\'ve been waiting a while...)
<STOP>
Jihye: *I sigh.*

Shit... I wonder how bad of a week it would have to be for a customer like him...

*It wasn\'t exactly surprising that customers like this were'] 

GPTJForSampling.from_pretrained('./pygmalion-6b-split', n_positions=256, batch_size=1, tp_degree=1, amp='f16')

neuron_model.sample(input_ids, sequence_length=256)
start = time.time()
neuron_model.sample(input_ids, sequence_length=256)

# sha256sum pytorch_model-00001-of-00002.bin
88ba2b44537f444e3fad92dff6962ac8c0b983427523484f98e7acf2d71fd65e  pytorch_model-00001-of-00002.bin