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What's the community thinking about RAGing, RAFTing or Fine-Tuning opensource models, for the specific purpose of DevOps, Sys-Admin, MLOps or for that matter any such task-domain?
From what I understood so far about gptscript, tools are the space where a user can express needs.
But in my (very) initial tests, just typing ls
on the gptscript prompt (llm-basics-demo
) is yielding this output.
my@dev1:~$ gptscript github.com/gptscript-ai/llm-basics-demo
Hello! I'm here to help you with any questions or information you might need. How can I assist you today?
> ls
It looks like you're using a command that is common in Unix-based systems to list directory contents. If you need help with
something specific related to this command or anything else, feel free to ask!
@Your Friendly Chat Assistant>
Every systems guy would expect a different output to the ls
prompt.
What are your thoughts on:
- the LLM "powering" gptscript having some background knowledge related to the intentions of the user?
- which of RAG, RAFT or Fine-tuning could/would work better? Or are foundational models (remember, their knowledge is old) already the best fit?
Thanks for your views!
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