Google TabFM predicts from tables without extra training
Google Research's TabFM is a for data arranged in rows and columns. It can handle and regression when a table mixes number columns and category columns. It does not need or search.
Example rows are given as context, and the model makes a prediction in one . This can reduce the work of training and testing a separate model for tabular prediction tasks.
Key points
- TabFM is a Google Research for tabular data.
- It supports and regression on mixed number and category columns.
- It uses example data as context instead of requiring .
- It avoids search, according to the description.
- It produces predictions in one .