OmniTab is a table-based QA model proposed in [OmniTab: Pretraining with Natural and Synthetic Data for Few-shot Table-based Question Answering](https://arxiv.org/pdf/2207.03637.pdf). The original Github repository is [https://github.com/jzbjyb/OmniTab](https://github.com/jzbjyb/OmniTab).
## Description
`neulab/omnitab-large-finetuned-wtq` (based on BART architecture) is initialized with `microsoft/tapex-large`, continuously pretrained on natural and synthetic data, and fine-tuned on [WikiTableQuestions](https://huggingface.co/datasets/wikitablequestions).
## Usage
```python
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
title = "{O}mni{T}ab: Pretraining with Natural and Synthetic Data for Few-shot Table-based Question Answering",
author = "Jiang, Zhengbao and Mao, Yi and He, Pengcheng and Neubig, Graham and Chen, Weizhu",
booktitle = "Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies",