> Aside from the minuscule context length, it also lacks the instruction tuning and reinforcement learning from human feedback (RLHF) that turn a large language model into a chatbot.
Strictly necessary? Maybe not. I wrote that before URIAL [1][2]. I actually haven't tried URIAL in GPT2 small but I need to give it a whirl. Might be too small a model to work?
Even if URIAL works with GPT2 small, the really small context length in the Excel file as currently implemented will make it hard to leverage. I've considered a more flexible implementation to support a longer context length (e.g. using Macros to build the layout of the sheet) but have prioritized the teaching videos first.
By default it's just going to be a text completion model, you want an additional round of training to make it behave like a chatbot. I guess you could probably get away with just fine-tuning on chatbot discussions, but everybody uses RLHF so I guess it must be much more efficient for that.
Even if URIAL works with GPT2 small, the really small context length in the Excel file as currently implemented will make it hard to leverage. I've considered a more flexible implementation to support a longer context length (e.g. using Macros to build the layout of the sheet) but have prioritized the teaching videos first.
[1] https://allenai.github.io/re-align/index.html [2] Summary https://twitter.com/intuitmachine/status/1732089266883141856