In celebration of receiving 10,000 stars on GitHub, the Ludwig community organized a mini-virtual hackathon, encouraging participants to fine-tune an open-source large language model (LLM) for unique projects. The winning project, Dickens, utilized the Zephyr-7B-Beta model to transform natural language data descriptions into data quality checks, aligning with the Great Expectations library. Ludwig's versatility and ease of use were highlighted across various projects, such as a GST FAQ chatbot, intent classification for customer support, democratizing feature engineering of tabular data, and assessing health data from smart devices. Each project leveraged Ludwig for its declarative approach, facilitating seamless model fine-tuning and integration, with winners receiving special edition Ludwig merchandise.