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license: apache-2.0 |
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--- |
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# Model description |
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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. |
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# Overview |
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*Language model*: t5-base \ |
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*Language*: English \ |
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*Task*: Table Question Generation \ |
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*Data*: WikiSQL |
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# Intented use and limitations |
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One can use this model to generate questions given a table. Biases associated with pre-training of T5 and WikiSQL dataset may be present. |
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## Usage |
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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). |
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## Citation |
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```bibtex |
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@inproceedings{chemmengath2021topic, |
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title={Topic Transferable Table Question Answering}, |
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author={Chemmengath, Saneem and Kumar, Vishwajeet and |
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Bharadwaj, Samarth and Sen, Jaydeep and |
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Canim, Mustafa and Chakrabarti, Soumen and |
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Gliozzo, Alfio and Sankaranarayanan, Karthik}, |
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booktitle={Proceedings of the 2021 Conference on |
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Empirical Methods in Natural Language Processing}, |
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pages={4159--4172}, |
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year={2021} |
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} |
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``` |
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