i'm figuring out how to train a LLM and documenting each step in this blog series. 

for anyone who is also curious, here is part 1:
https://michaelhly.com/posts/train-llm-one

@operator & /operator | 💭 about BCI, bioinformatics, search, chaos, decentralized AI | join me in /entropybender /llm

download meeeee @ blobs.lol;
win up to $75 every week!!!

oops. if anyone else hits the 404
https://michaelhly.com/posts/tune-llm-one

a). just exploration
b). i'm not sure what you mean by limit. but hugging face has pretrained llamas that you can grab off the shelf:
https://huggingface.co/meta-llama

my belief is that you should tune a model to find a fit for your dataset ... otherwise you probably don't need to ...

blobs, are you doing AI for blobs (the product) or is it exploration?

also: what limit should i reach before i consider tuning Llama? what does it look like?