The heaviest domain. Choosing a model and setting its inference parameters, prompt engineering and the attacks against it, Retrieval Augmented Generation, the four ways to customise a model, and how to evaluate the result.
A service extracts the invoice number, date and total from uploaded documents and passes the result to an accounting system. The output must be consistent, because a downstream parser depends on it. Which inference setting is most appropriate?
AA temperature at or near zero, so the model consistently picks the likeliest continuation.
BA high temperature, so the model considers more possible readings of the document.
CA high top p value, to widen the set of tokens the model may choose from.
DA raised maximum output length, so the model has room to correct itself.