【进阶-思维链(Chain of Thoughts CoT) 】本系列视频主要介绍prompt工程相关基础及进阶用例,旨在帮助大家更好地了解和使用prompt 12:24 【进阶-自洽性(Self-Consistency) 】本系列视频主要介绍prompt工程相关基础及进阶用例,旨在帮助大家更好地了解和使用prompt 13:45 【进阶-思维树(Tree-of-thought, ToT) 】本...
代码地址:https://github.com/princeton-nlp/tree-of-thought-llm
Tree of Thoughts: Deliberate Problem Solving with Large Language Models 代码:https://github.com/princeton-nlp/tree-of-thought-llm。 0摘要 语言模型越来越多地被用于解决各种任务中的一般问题,但仍然局限于推理过程中的令牌级、从左到右的决策过程。这意味着他们可能在需要探索、战略展望或初始决策起关键作用...
Tree of Thoughts: Deliberate Problem Solving with Large Language Models - NopenAI/tree-of-thought-llm
tree of thoughts method. Each expert will share their thought process in detail, taking into account the previous thoughts of others and admitting any errors. They will iteratively refine and expand upon each other's ideas, giving credit where it's due. The process continues until a conclusive...
代码:https://github.com/princeton-nlp/tree-of-thought-llm 提出了一个关于语言模型(LM)的新框架:Thought of Tree(ToT),旨在让LM在解决问题时能够进行更加系统和有目的的规划。 作者指出,虽然现有的LM可以执行各种任务,但它们仍然采用了最初的自回归生成文本的机制,即逐个决策地生成文本。
然而,目前的方法例如 Chain-of-thought 等通常缺乏对于中间过程的验证。并且大型语言模型的部署和推理成本相对较高,特别是在利用无参数更新的推理增强技术时。这些技术需要大量的上下文和多步的答案生成,进一步增加了推理成本和时间。 因此,本文研究面向轻量化大模型的复杂任务推理,使用较小规模的模型(7B),构建双系统...
git – github – source tree August 14th, 2017 I thought of calling this article The value of tools. I started with git at the command prompt. The threshold was high. Not only was the way of treating my precious source code files new but I also had to learn new commands and how to...
file that I have to handle with javascript to make it hierarchical, in order to later build a tree. Every entry of the json has : id : a unique id, parentId : the id of the parent node (which is 0 if the node is a root of the tree) level : the level of depth in the tree...
So I thought of compiling the Qt source package on shiny new Raspberry Pi 2, which has quad-cores and 1GB of RAM so I thought it will be faster to compile directly on it, and ran the./configureandmake -j3(-j3 here is telling make command to use 3-cores to compile) with following...