JFrog MLOps | ML Artifact Management
Manage ML Models As Part of Your Secure Software Supply Chain
Create a single system of record for ML models that brings ML/AI development in line with your existing SDLC. ML Model Management allows you to store first party models and proxy Hugging Face with scanning for security and license issues.
Unify ML, Dev, Sec, and Ops
Bring the management of AI/ML models alongside PyPI, CRAN, Conan, Conda, and other software components for a unified view of the software you’re building and releasing. Apply the same best practices you use for package management to model management.
Benefit from
ALL your software components in one place
Proxy Hugging Face to ensure availability of models you rely on
Enhanced control, traceability and security of ML models
Integrated malicious model detection and license compliance
Standardize MLOps processes with existing tooling
Model Management at Scale
Unlike Git and point solutions, leveraging JFrog for model management provides the best in performance, scalability, and optimized handling of large binary files. Store models alongside their required data, files, and packages to easily bundle them into a secure Release Bundle for maturation towards release distribution.
Integrated with Amazon SageMaker
Connect JFrog Artifactory with Amazon SageMaker to ensure that artifacts consumed or produced when using SageMaker tools are pulled from and saved in Artifactory for immutable, traceable, and secure releases.
Powering the Software that Powers the World
It’s our Liquid Software vision to automatically deliver software packages seamlessly and securely from any source to any device.
Additional Resources
Blog\Read the blog on ML Model Management\Read Now
Documentation\Explore the technical documentation\Read Now
Futher Reading\Explore JFrog Artifactory\Read Now
Frequently Asked Questions
Which Model repositories/zoo API interfaces does JFrog support?
JFrog currently supports Hugging Face as a model repository. Organizations can upload their proprietary or modified models via local repos, as well as proxy Hugging Face with remote repos for 3rd party models.
What file formats does JFrog support for models?
JFrog supports all file formats (ie. pkl, onnyx) and frameworks as a derivative of Hugging Face.
Do JFrog Hugging Face local repositories support federation?
Yes, the model and data files will be included in federations.
Does JFrog act as a machine learning model repository or registry?
JFrog serves as a ML Model registry with all the benefits of Artifactory and Xray applied to an organization’s models.