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  • Resize,w 360,h 240
    RAG 簡介

    Retrieval Augmented Generation 檢索增強(qiáng)生成 RAG 首次在 2020 發(fā)表的一篇名為 Retrieval-Aug...

  • vim

    colorscheme colorschemes[https://github.com/rafi/awesome-vim-colorscheme...

  • oh-my-zsh

    2. oh-my-zsh oh-my-zsh[https://github.com/ohmyzsh/ohmyzsh] 2. Theme http...

  • Resize,w 360,h 240
    mac ls no color

    1. unselect the following option 2. select the following option

  • loki log retention

    method 1 method 2 method 3

  • fluent-bit loki plugin build

    development fluent-bit build fluent-bit loki plugin method:1. use the or...

  • Kubernetes: Anti-Patterns

    Anti-Patterns Not Setting Resource Requests Omit Health Checks Using the...

  • force delete namespace

    reference There is no way to force delete Namespaces with invalid finali...

  • yum 麒麟

    https://blog.csdn.net/weixin_42328170/article/details/120728654[https://...

個(gè)人介紹
Base LLM has been trained to predict the next word base on text training data, often trained on a large amount of data from the internet and other sources to figure out what's the next most likely word to follow

Instruction Tuned LLM:
has been trained to follow instructions
You start off with a base LLMs that has been trained on a huge amount of text data and further train it further fine tune it
with input and outputs that are instructions and good attempts to follow those instructions call RLHF reinforcement learning to make the system better able to be helpful and follow instructions because instruction tuned LLMs have been trained





If you can't explain it simply, you don't understand it well enough.

Figure out what you love doing and don’t suck at, then try to figure out how to make a living doing that! Don’t be scared. We’re all going to die, it’s just a question of when and how

All problems in computer science can be solved by another level of indirection
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