the previous X is the result of a top-k N id's or categories (we used various models) and with the output apply some business rules, like seasson, recently, etc

We solved with lightgbm, for news to suggest.

if you have the tabular data, (user properties, buyed product, previous X products viewed), sets the buyed product as target and you had your recommender done.

There's a lot of examples doing it with lightgbm or xgboost (gbm is faster)

About text generation: Can someone share experiences with Bloom, Palm, and others than Gpt-3

I'm trying to build a niche text generator in Spanish using open-source models, but the internet conversation is dominated by gpt-3, and few articles about Prompt engineering, or model comparisons