Combining learning approaches

[jemrobinson]

We used two models, one trained on files with traceability back to the original source (llama) and one trained on Q&A generated from files (curie). One way to combine these two might be:

• collect all relevant files
• run a preprocessing step that creates Q&A for each file.
• create a new file containing the original data + the Q&A
• train the llama model on this

This could give us the "here's where I pulled the answer from" structure of llama plus the nice answers coming from the curie model. Thoughts?