Tabular-LLM
The project collaborates with the Alpaca-CoT platform to enhance language models' understanding of tabular data. With a focus on organizing diverse, open-source datasets for table-related tasks, such as table QA and table-to-text generation, it transforms these datasets into an instruction tuning format. This approach refines LLMs to improve their ability in handling tables, assisting researchers in developing domain-specific models. By supporting the open-source community, the initiative aims to regenerate models with better table processing capabilities, providing expanded data and model resources.
