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Is that we should fully use all 70b parameter? I mean can we use some skill like discrimination to make it smaller Or use another some small model to help its inference Or separate the whole big model into some small part and use Moe to help it move faster? #1
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@Kevin-shihello-world |
Can we change it a little bit? I mean it hasn't written into the rules of this competition. I mean we can for sure that we won't change the model architecture too much and we would not reduce the total parameter. |
And I apologize it that last time I didn't review it carefully for the question and some reply After I transform those spoken language to words |
I am sorry but the answer is no. The point of the challenge is inference optimizations and strategies, MoE is not included.
It's afraid that the fourth question is not about LLM inference and I cannot anwer your question. You can contact the concerned person by email [email protected]
You can change the baseline code or just start from strach to build a inference engine which proper to your machine system. The ASC24 committee does not set too many limits and kinds of methods can be used as long as it is clearly presented in the proposal. |
Okay, thanks all organized for this competition!And I also wants to know Can we add a little bit permit to it? I mean like sometimes I may thought we can use an auto encoder to encode Some data and make them smaller. So as we can deliver it with cheaper bus price in distributed system when inference . |
@Kevin-shihello-world if you mean to truncate or shorten the samples, the answer is it's not permitted for fairness. BTY, if you have any question you can contact the email [email protected]. It will be replied as soon as possible. |
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