I’m curious if there’s an ideal setup or pipeline that you can get an LLM to listen and “learn” from you if you just feed it info everyday like a personal diary? Would be interested to see how the model recalls or processes details of my life. Would you just use a web ui like oogabooga to feed info and adapt the model?
Do you have a specific use case or need in mind? If you want it to remember things, you wouldn’t necessarily ‘feed it into an LLM’ but if you want it to produce output more like how you’d speak, then fine-tuning would probably be appropriate.
Depending on what you wanna do, it will have different design requirements.
In general, I’d ask what’s the desired goal first.
You will need to feed the model with the conversation log every time you query it, and as such you’d be limited by the context length on the model.
With a 100k context model you’d be able to keep a chat log of about 70-100 000 words, which is about the length of a normal book.