How to pre-train or finetune LLM with structured dataset, so the LLM can reason the relationships between data objects
I want to train LLM with structured dataset such as database with multiple tables. Here is an simple example:t_user:idname1Jason2Eric3Davidt_book:idtitle1Gone with The Wind2Brave New World3Native Sont_bookstore:idname1The Book Nook2The Literary Loft3Wordsmith Bookst_order:user_idbookstore_idbook_id121122233After training the LLM, it can reason on this relational database. Such as when I ask:how many books didJasonbuy inThe Literary Loftbootstore? It can answers: 2 books,Gone with The WindandBrave New World.How can I prepare the corpus from the database and train the LLM ?I have searched for some solutions, such as ask the LLM to transform prompts to sql queries, but that’s not what I want.
2023-12-01T09:40:51Z
what aboutWhat is Table Question Answering? - Hugging Face
2023-12-04T01:41:05Z
Table Question Answering seems can handle only one table, can’t reason relationships between multiple tables, are there any other suggestions?
2023-12-05T02:07:57Z
There is at least one model for multi table qa.will this work for your data?huggingface.covaishali/multitabqa-base · Hugging FaceWe’re on a journey to advance and democratize artificial intelligence through open source and open science.