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by rnosov
1215 days ago
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I think they are correctly referring to ChatGPT as GPT-3 + RLHF. In other words
ChatGPT = GPT-3 + RLHF. So, 80GB A100 GPU would be required for both GPT-L AND RLHF (PyTorch version). And it looks to me from the TFA that the main thing that takes a lot of space is actually RLHF. >I don’t understand how they went from talking about 175B params across 32 cards to 774M on one card. 175B divided by 32 is 5.4B. They claim 774M is the size of GPT-L which if run in conjunction with their RLHF would require 80GB A100 GPU to train (using their RLHF PyTorch implementation). They additionally claim that training GPT-3(175B params) plus RLHF would need 64 * 80gb = 5120gb of memory if using PyTorch implementation of RLHF or 32 * 80gb = 2560gb if going Colossal AI route. To be honest, these numbers do look to me to be a bit of a cheesy ad for their product but hey they need to put food on their table too. I'm not sure if the dataset would be such a huge problem otherwise Britannica would still be ahead of Wikipedia. Given an army of volunteers willing to produce it OpenAI brigade of contractors has no chance. |
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