| | --- |
| | 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} |
| | } |
| | ``` |
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