/table_question_answering_tapas

table_question_answering_tapas

Primary LanguageJupyter Notebook

👍 Table Question Answering using TAPAS

Open in colab

The TAPAS model was proposed in TAPAS: Weakly Supervised Table Parsing via Pre-training by Jonathan Herzig, Paweł Krzysztof Nowak, Thomas Müller, Francesco Piccinno and Julian Martin Eisenschlos. It’s a BERT-based model specifically designed (and pre-trained) for answering questions about tabular data.

Compared to BERT, TAPAS uses relative position embeddings and has 7 token types that encode tabular structure. TAPAS is pre-trained on the masked language modeling (MLM) objective on a large dataset comprising millions of tables from English Wikipedia and corresponding texts.


TAPAS has been fine-tuned on several datasets:

  • SQA (Sequential Question Answering by Microsoft)
  • WTQ (Wiki Table Questions by Stanford University)
  • WikiSQL (by Salesforce).

Read more about TAPAS model from HuggingFace


Sample image from Demo

Sample from demo