Show HN: Fast HuggingFace model downloader with Web UI and parallel downloads (github.com)

A new tool has emerged that significantly enhances the process of downloading models and datasets from the Hugging Face Hub. Dubbed the "Hugging Face Model Downloader," this utility features a sleek web user interface (UI), supports resumable and multipart downloads, and allows for parallel processing to speed up retrieval. Users can start the web interface instantly through a simple command and manage filters, connections, and output locations with various customizable options. The tool is built in Go and provides both a command-line interface and a web-based experience that tracks real-time download progress. For the AI/ML community, this downloader is significant as it streamlines the access and utilization of machine learning models, which is crucial for developers and researchers working with AI. By improving the efficiency of downloading models—especially large ones—this tool reduces time and technical overhead, making it easier to integrate state-of-the-art AI capabilities into applications. The flexibility in utilizing a REST API for programmatic downloads indicates strong potential for automation in machine learning workflows, enabling users to incorporate this functionality into broader development pipelines effectively.