TAPEX (base sized model) TAPEX was proposed in TAPEX: Table Pre training via Learning a Neural SQL Executor by Qian Liu, Bei Chen, Jiaqi Guo, Morteza Ziyadi, Zeqi Lin, Weizhu Chen, Jian Guang Lou. The original repo can be found here. Model description TAPEX ( Ta ble P re training via Ex ecution) is a conceptually simple and empirically powerful pre training approach to empower existing models with table reasoning skills. TAPEX realizes table pre training by learning a neural SQL executor over a synthetic corpus, which is obtained by automatically synthesizing executable SQL queries. TAPEX is based on the BART architecture, the transformer encoder encoder (seq2seq) model with a bidirectional (BERT like) encoder and an autoregressive (GPT like) decoder. This model is the tapex base model fine tuned on the WikiSQL dataset. Intended Uses You can use the model for table question answering on relatively simple questions. Some solveable questions are shown below (corresponding tables now shown): Question Answer : : : : tell me what the notes are for south australia no slogan on current series what position does the player who played for butler cc (ks) play? guard forward how many schools…
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