Developed and delivered the Croissant Metadata Saving feature for Hugging Face Datasets within the ServiceNow/Fast-LLM repository, focusing on enhancing dataset preparation workflows. The solution automated the retrieval of metadata either from the Hugging Face Hub API or by copying from local dataset directories, then generated a structured croissant.json file in the output directory. This approach improved reproducibility and streamlined downstream machine learning pipelines by ensuring consistent metadata handling. The work leveraged Python for API integration, data preparation, and file handling, with an emphasis on robust automation. The month’s efforts were feature-driven, with no major bugs reported during implementation.