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You pass embd of length one during the generation of content. I placed prints there it was printing 1.
So I guess all the data is stored inside the model class. With model.ctx or wtr, I am not sure how it all works yet.
Anyway for Monte Carlo Tree Search I sometimes want to choose most prospective state of the model class. So I need Save/Load functions of this state. I can start everything from scratch again passing all data token by token, but this is heavy function it takes most of the time of the run, so I don't want to waste time to increase the length only to the best candidates, but it takes a lot of memory, so I need to save the state to a disk. Please advice...
I could run simpler MCTS to begin with, maybe it's what I will do first, or waste time only on the best candidates only. But I would like to be able to Save/Load the state to file, from the middle of the run, and continue from there. The basic idea is to try reproduce the RL with chess/GO engines MCTS. They say the function there playing very weak, but with MCTS it's like magic. It could be the case for llama models, many people would just wait a day or two for a slower response, but for free and of quality of GPT4.
The text was updated successfully, but these errors were encountered:
simsim314
changed the title
Issues on Monte Carlo Tree Search on alpaca.cpp
Issues with Monte Carlo Tree Search on alpaca.cpp
Apr 11, 2023
So I've managed to run alpaca.cpp from Visual Studio, and it all looks great and interesting.
But then I see in code that you provide the:
llama_eval eval function here:
https://github.com/antimatter15/alpaca.cpp/blob/master/chat.cpp#L954
You pass embd of length one during the generation of content. I placed prints there it was printing 1.
So I guess all the data is stored inside the model class. With model.ctx or wtr, I am not sure how it all works yet.
Anyway for Monte Carlo Tree Search I sometimes want to choose most prospective state of the model class. So I need Save/Load functions of this state. I can start everything from scratch again passing all data token by token, but this is heavy function it takes most of the time of the run, so I don't want to waste time to increase the length only to the best candidates, but it takes a lot of memory, so I need to save the state to a disk. Please advice...
I could run simpler MCTS to begin with, maybe it's what I will do first, or waste time only on the best candidates only. But I would like to be able to Save/Load the state to file, from the middle of the run, and continue from there. The basic idea is to try reproduce the RL with chess/GO engines MCTS. They say the function there playing very weak, but with MCTS it's like magic. It could be the case for llama models, many people would just wait a day or two for a slower response, but for free and of quality of GPT4.
The text was updated successfully, but these errors were encountered: