 Model description - It is a BERT-based model specifically designed (and pre-trained) for answering questions about tabular data - TAPAS uses relative position embeddings and has 7 token types that encode tabular structure. - It is pre-trained on the masked language modeling (MLM) objective on a large dataset comprising millions of tables from English Wikipedia and corresponding texts.  The model has been fine-tuned on several datasets  1. SQA (Sequential Question Answering by Microsoft)  2. WTQ (Wiki Table Questions by Stanford University)  3. WikiSQL (by Salesforce).   