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View Code? Open in Web Editor NEW[ICLR 2023] ReAct: Synergizing Reasoning and Acting in Language Models
License: MIT License
[ICLR 2023] ReAct: Synergizing Reasoning and Acting in Language Models
License: MIT License
Hello, I would like to ask if there is a code implementation for cot ->react and react ->cot mentioned in the paper
你好,我想问一下论文里提到的cot->react 和 react->cot 有代码实现吗
Hello, thank you for this important work and project!
I'm already seeing many references to the paradigm. The problem is that there was already a massively popular project named React. This makes searches for ReAct somewhat difficult.
Hi there, I cannot seem to find any information on the fine-tuning process in your paper and this repository.
A snippet from your paper:
However, when finetuned with just 3,000 examples, ReAct becomes the best
method among the four, with PaLM-8B finetuned ReAct outperforming all PaLM-62B prompting
methods, and PaLM-62B finetuned ReAct outperforming all 540B prompting methods. In contrast,
finetuning Standard or CoT is significantly worse than finetuning ReAct or Act for both PaLM-
8/62B, as the former essentially teaches models to memorize (potentially halluincated) knowledge
facts, and the latter teaches models how to (reason and) act to access information from Wikipedia, a
more generalizable skill for knowledge reasoning.
@ysymyth Thanks for your good work!
Can you attach the output of HotpotQA (hotpotqa.ipynb), like those in (FEVER.ipynb)? Thank you!
Did you use prompt like https://github.com/hwchase17/langchain/blob/bc2ed93b77cf9c40920ca5bf96968c90bb3e322e/langchain/agents/react/textworld_prompt.py#L4-L45 to ask GPT3 to generate result in ReAct format?
Or you just create many examples, and fine tune it, so it generate it? And this only works in your fine tuned model, and not working in GPT3-4?
I'd like to know if the method in langchain actually correct and works.
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.
Don't give me links to Alfworld! The installations there don't work, the support is nonexistent.
How can I install ReAct on my Ubuntu 22.04?
I was wondering if autogpt is inspired by your ideas. anyway, thanks for your great efforts.
Hello @ysymyth, thanks for sharing your code, excellent work! Is there any plan to release the code of FEVER and WebShop? Thank you!
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