TAPEX: WikiSQL Data enabled Base Finetuned (Table Pre-training via Learning a Neural SQL Executor) Model
A large-sized TAPEX model fine-tuned on the WikiSQL dataset, optimized for translating natural language questions into SQL queries for effective table-based question answering.
About Model
The TAPEX Large Fine-Tuned on WikiSQL model enhances the TAPEX architecture by focusing on the translation of natural language questions into executable SQL queries. Trained on the WikiSQL dataset, which contains a vast collection of questions and corresponding SQL queries over tables, this model excels in understanding user inquiries and generating accurate SQL commands to retrieve the desired information. The fine-tuning process equips the model with the ability to navigate various table schemas and question complexities, making it an invaluable tool for applications that require dynamic data retrieval, interactive data exploration, and seamless database querying through natural language interfaces.
TAPEX: WikiSQL Data enabled Base Finetuned (Table Pre-training via Learning a Neural SQL Executor) Model
Metadata
MIT
Qian Liu and Bei Chen and Jiaqi Guo and Morteza Ziyadi and Zeqi Lin and Weizhu Chen and Jian-Guang Lou
Fine-Tuned Model
N.A.
Open
Sector Agnostic
12/03/25 06:34:51
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Activity Overview
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5 
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Tags
- SQLQueryGeneration
- TAPEX
- WikiSQL
- FineTunedModel
- DataRetrieval
- BART
- Transformers
- NaturalLanguageProcessing
License Control
MIT
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