readme: ---
  license: apache-2.0
  ---
  
  # Model description
  
  This is an [t5-base](https://huggingface.co/t5-base) model, finetuned to generate questions given a table using [WikiSQL](https://huggingface.co/datasets/wikisql) dataset. It was trained to take the SQL, answer and column header of a table as input to generate questions. For more information check our T3QA [paper](https://aclanthology.org/2021.emnlp-main.342/) from EMNLP 2021.
  
  # Overview
  
  *Language model*: t5-base \
  *Language*: English \
  *Task*: Table Question Generation \
  *Data*: WikiSQL
  
  # Intented use and limitations
  One can use this model to generate questions given a table. Biases associated with pre-training of T5 and WikiSQL dataset may be present.
  
  ## Usage
  One can use this model directly in the [PrimeQA](https://github.com/primeqa/primeqa) framework as in this example [notebook](https://github.com/primeqa/primeqa/blob/tableqg/notebooks/qg/tableqg_inference.ipynb).
  
  ## Citation
  ```bibtex
  @inproceedings{chemmengath2021topic,
    title={Topic Transferable Table Question Answering},
    author={Chemmengath, Saneem and Kumar, Vishwajeet and
            Bharadwaj, Samarth and Sen, Jaydeep and
            Canim, Mustafa and Chakrabarti, Soumen and
            Gliozzo, Alfio and Sankaranarayanan, Karthik},
    booktitle={Proceedings of the 2021 Conference on 
        Empirical Methods in Natural Language Processing},
    pages={4159--4172},
    year={2021}
  }
  ```
  
  