The original paper mentions that tables with maximum 500 cells were used to train the model. There is also a 512 token limit in the TAPAS config file, which implies that a table can have no more than 512 cells while predicting/inferencing. Just wanted to understand how to use TAPAS for large tables, for instance, for tables with ~100 Million rows and ~100 columns, if at all it is possible.
The original paper mentions that tables with maximum 500 cells were used to train the model. There is also a 512 token limit in the TAPAS config file, which implies that a table can have no more than 512 cells while predicting/inferencing. Just wanted to understand how to use TAPAS for large tables, for instance, for tables with ~100 Million rows and ~100 columns, if at all it is possible.