Hugging Face is an open-source platform that provides tools and resources for building, training, and deploying machine learning models. By integrating Hugging Face with JFrog Artifactory, you can create a secure, private, and centralized repository for your ML models. This enables you to manage your organization's proprietary models alongside proxied models from the public Hugging Face Hub. With these capabilities, Artifactory provides a single source of truth for your MLOps workflows with enhanced security, governance, and reliability. For more information, see the Hugging Face documentation.
Using Artifactory with Hugging Face provides the following benefits:
Unified Repository Management: Consolidate all your Hugging Face models, datasets, and related files using Artifactory as a system of record. Set up secure local repositories, access a cached version of Hugging Face Hub, and create a virtual repository as a single point of access to all your resources.
Xray Scanning: Secure your machine learning model lifecycle by scanning the licenses of machine learning models and scanning for malicious models.
Support for Hugging Face Client: Use the Hugging Face CLI and Python Hugging Face Hub to seamlessly deploy, resolve, and manage your ML models in Artifactory.
Robust Access Control: Secure your repositories with fine-grained permissions and manage who can access, deploy, and manage specific models and repositories.
Enterprise Readiness: Scale your Hugging Face use in Artifactory with enterprise-grade features like high availability, multi-site repository replication, and massively scalable storage options to support global teams and large-scale projects.