junxiaoyao/regression2chatgpt @ en

Gen TANG 636815ed79 finish annotation for ch11		%!s(int64=2) %!d(string=hai) anos
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README.md	4edb97c350 typo	%!s(int64=2) %!d(string=hai) anos
char_gpt.ipynb	21e1edfb15 finish char-gpt annotation	%!s(int64=2) %!d(string=hai) anos
gpt2.ipynb	cb693386eb translate comment into eng	%!s(int64=2) %!d(string=hai) anos
gpt2_lora.ipynb	636815ed79 finish annotation for ch11	%!s(int64=2) %!d(string=hai) anos
gpt2_lora_optimum.ipynb	636815ed79 finish annotation for ch11	%!s(int64=2) %!d(string=hai) anos
gpt2_reward_modeling.ipynb	636815ed79 finish annotation for ch11	%!s(int64=2) %!d(string=hai) anos
lora_tutorial.ipynb	636815ed79 finish annotation for ch11	%!s(int64=2) %!d(string=hai) anos

Directory	Description
char_gpt.ipynb	Creating GPT-2 from scratch and conducting autoregressive learning for python script (predict the next char based on context)
gpt2.ipynb	Usage of open-souce GPT-2 model
lora_tutorial.ipynb	Implementation of LoRA (simple version) and usage of LoRA in peft
gpt2_lora.ipynb	SFT (supervised fine-tuning) of GPT-2 by using LoRA (Note: This script is NOT optimal)
gpt2_lora_optimum.ipynb	More elegant SFT on GPT-2 by using LoRA
gpt2_reward_modeling.ipynb	Reward modeling on GPT-2 by using LoRA