dsdanielpark

docker --version It can be slightly different depending on the Docker version and programs such as cmd, powershell, linux, etc. Check it through the help command and modify it little by little.

Check This Useful Repository!
https://github.com/DSDanielPark/GPT-BERT-Medical-QA-Chatbot/blob/main/README.md

Docker hub

1. https://hub.docker.com/
2. https://docs.docker.com/engine/reference/commandline/manifest/

dsdanielpark

1. Install streamlit

pip install streamlit 
pip install streamlit-chat

2. check status

dsdanielpark

https://ecotrust-canada.github.io/markdown-toc/

dsdanielpark

Remix Documentation

• https://remix.run/
• gitpod https://www.gitpod.io/

dsdanielpark

• http://www.softsea.com/review/Mongoose.html
• https://mongoose.ws/
• https://github.com/cesanta/mongoose

dsdanielpark

SSH rsa key gen in local storage

   2 cd ~/.ssh
   
   3 ls -al

   # SSH Keygen
   5 ssh-keygen -t rsa -C "[email protected]" -f "id_rsa_gitId1"

dsdanielpark

How to unstar all repository.

Reference: https://gist.github.com/justlaputa/a6da84981eca963817e652b5f2452cfc

1. Generate authorization token for unstar. https://github.com/settings/tokens

2. Export variable

export APIKEY=xxxxxxxxx

dsdanielpark

Shpinx

Installation

pip install Sphinx

Quick start

mkdir docs
cd docs

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People

:bowtie:	😄 :smile:	😆 :laughing:
😊 :blush:	😃 :smiley:	☺️ :relaxed:
😏 :smirk:	😍 :heart_eyes:	😘 :kissing_heart:
😚 :kissing_closed_eyes:	😳 :flushed:	😌 :relieved:
😆 :satisfied:	😁 :grin:	😉 :wink:
😜 :stuck_out_tongue_winking_eye:	😝 :stuck_out_tongue_closed_eyes:	😀 :grinning:
😗 :kissing:	😙 :kissing_smiling_eyes:	😛 :stuck_out_tongue:

dsdanielpark

Maybe you've heard about this technique but you haven't completely understood it, especially the PPO part. This explanation might help.

We will focus on text-to-text language models 📝, such as GPT-3, BLOOM, and T5. Models like BERT, which are encoder-only, are not addressed.

Reinforcement Learning from Human Feedback (RLHF) has been successfully applied in ChatGPT, hence its major increase in popularity. 📈

RLHF is especially useful in two scenarios 🌟:

• You can’t create a good loss function
  • Example: how do you calculate a metric to measure if the model’s output was funny?
• You want to train with production data, but you can’t easily label your production data