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Hi, I was wondering how could we finetune the small REACT model given the prompts generated using LLM being prompt tuned.
Are we trying to use LoRA or P-Tuning for the finetuning step?
How to use the prompt data?
(1) Letting all the actions and thoughts be the input and let the final action (answer) be the output
(2) Parse the whole ReAct process and use previous in-context info as input and current action as output
(3) Or any other way you used?
Really appreciate your help.
The text was updated successfully, but these errors were encountered:
Hi, I was wondering how could we finetune the small REACT model given the prompts generated using LLM being prompt tuned.
Are we trying to use LoRA or P-Tuning for the finetuning step?
How to use the prompt data?
(1) Letting all the actions and thoughts be the input and let the final action (answer) be the output
(2) Parse the whole ReAct process and use previous in-context info as input and current action as output
(3) Or any other way you used?
Really appreciate your help.
The text was updated successfully, but these errors were encountered: