Artifactory has expanded its support for Hugging Face repositories to include both datasets and models, emphasizing the importance of training machine learning models with quality datasets. This integration allows Artifactory users to proxy Hugging Face Datasets for both remote and local repositories using the Hugging Face Python library, ensuring dataset consistency and reliable performance. This setup provides fine-grain control over access to models and datasets, centralizing management and resolution of these assets. Hugging Face offers datasets either directly within its registry or through external links, with Artifactory caching the former and providing a pass-through for the latter. The initiative aims to enhance the linkage between models and their training datasets, and users can explore these features through a JFrog account or a free 14-day trial.