Tabula Rasa: Large Language Models for Tabular Data | by Salvatore Raieli | Mar, 2024

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Tabular data are everywhere, why and how you can use LLMs for them

Large Language Models for Tabular Data
image created by the author with AI

LLMs are increasingly used for both generative and reasoning tasks. The world stands on Excel, so why not combine the two?

In this article, we explore how we can use LLMs to conduct reasoning or other tasks on tables of various types. A fascinating journey into the newest models and databases that hold up the world.

Large Language Models for Tabular Data
Photo by Timothy Dykes on Unsplash

“It’s Excel’s world, we just live in it.”
— jgalt212 on

LLMs are large-scale, pre-trained, statistical language models based on neural networks. (source)

In short, a Large Language Model (LLM) is a transformer that has more than 10 B parameters and has been trained on a huge amount of text in an unsupervised manner. In other words, it is a transformer that has been scaled by training time, number of parameters, and data size. Scaling had a positive impact on downstream tasks and brought out several new properties (such as in-context learning):

Early language models mainly aim to model and generate text data, while latest language models (e.g., GPT-4) focus on complex task solving. From language modeling to task solving, it is…

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