Retrieval Augmented Generation 檢索增強生成 RAG 首次在 2020 發表的一篇名為 Retrieval-Augmented Generati...
發簡信
IP屬地：河南
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RAG 簡介 -
oh-my-zsh
2. oh-my-zsh oh-my-zsh[https://github.com/ohmyzsh/ohmyzsh] 2. Theme https://github.com/...
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fluent-bit loki plugin build
development fluent-bit build fluent-bit loki plugin method:1. use the origin fluent-bit...
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Kubernetes: Anti-Patterns
Anti-Patterns Not Setting Resource Requests Omit Health Checks Using the Latest Tag Ove...
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force delete namespace
reference There is no way to force delete Namespaces with invalid finalizers #77086[htt...
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yum 麒麟
https://blog.csdn.net/weixin_42328170/article/details/120728654[https://blog.csdn.net/w...
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kuberbuilder webhook proposal
Handle external API types explicitly in create api[https://github.com/kubernetes-sigs/k...
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kubernetes admission webhook 開發教程(自簽名)原創請勿轉載 完成代碼示例: https://github.com/allenhaozi/webhook[https://github.com/allenhaozi/webh...
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Python Decorators
裝飾器(Decorators)是 Python 的一個重要部分。簡單地說：他們是修改其他函數的功能的函數。他們有助于讓我們的代碼更簡短，也更Pythonic（Python范兒...
個人介紹
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
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