# Table QA

TAPEX is a model that achieves table pretraining by learning neural SQL executors, based on the BART architecture, specifically designed for table reasoning tasks.

TAPAS is a table-based question answering model that handles conversational QA tasks on tabular data through pre-training and fine-tuning.

TAPAS is a BERT-like Transformer model designed for table-based question answering tasks. It is pre-trained in a self-supervised manner on English Wikipedia table corpora and fine-tuned on the WikiSQL dataset.

TAPEX-large is a table QA model fine-tuned on the WikiSQL dataset, capable of understanding natural language questions and generating SQL queries or direct answers based on tabular data.

TAPAS is a QA model for tabular data. This tiny version is fine-tuned on the SQA dataset, suitable for table-based QA tasks in conversational scenarios.

This model is based on the tapas-base architecture, optimized for table input through pre-training, enhancing reasoning capabilities for QA tasks.