Hugging Face has released version 1.0 of the huggingface_hub library, marking a significant milestone after five years of development. This library now supports over 200,000 dependent libraries and provides access to more than 2 million public models, 500,000 public datasets, and 1 million public Spaces. The new version introduces breaking changes, including a shift to httpx for backend operations and a redesigned command-line interface that enhances functionality. It remains mostly backward compatible, with the exception of the transformers library, which requires specific versions for compatibility. The library's evolution is rooted in a desire to simplify sharing machine learning models. Initially, models were isolated on local machines, leading to inefficiencies and duplication of effort. The introduction of huggingface_hub in 2020 aimed to change that by creating a dedicated library for sharing models and datasets. Over the years, features have expanded significantly, moving from basic Git interactions to a comprehensive platform that includes APIs for managing repositories, hosting interactive demos, and serving models through various inference providers. Recent advancements include the Xet protocol, which optimizes file transfers by uploading only changed chunks of large files, enhancing performance without disrupting existing workflows. The library has seen tremendous growth, with 113.5 million monthly downloads and usage by more than 60,000 daily users. Huggingface_hub has become a vital component for major machine learning frameworks, with over 200,000 repositories on GitHub relying on it. As it moves into its next decade, the focus remains on building a robust foundation for the open machine learning community.