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Jozu Hub–Your private, on-prem Hugging Face registry
- Jozu Hub is a private, on-prem Hugging Face registry that focuses on securing and deploying Hugging Face models, creating a robust pipeline for model serving with strong security measures.
- The combination of KitOps, Dagger.io, and Ray simplifies MLOps pipelines, aiding in AI project deployment and model scaling.
- This guide demonstrates how to curate and secure models from Hugging Face by importing them into ModelKit and hosting them in a private registry like Jozu Hub.
- Using KitOps and Hugging Face together enhances model development efficiency, enabling direct imports and ensuring consistency in model artifacts and their dependencies.
- Jozu Hub addresses the need for a private, on-premises solution to host selected models due to the challenges posed by the vast number of models on Hugging Face.
- To import a model from Hugging Face using KitOps, one can run the 'kit import' command to download and package the model into a ModelKit for secure storage.
- After importing the model, push it to the registry using the 'kit push' command, specifying the repository name and tag for seamless deployment.
- An alternative method for importing models directly from Hugging Face via Jozu Hub's web interface streamlines the process, allowing quick additions to private repositories.
- Managing Hugging Face models through ModelKit packaging offers a structured approach for tracking versions and maintaining consistent environments, aiding teams moving from experimentation to production.
- For teams seeking consistency in deployment processes, this workflow can be beneficial for various applications, enabling efficient handling of machine learning models.
- Active communities on Discord and documentation on the KitOps website can provide further insights and support on KitOps implementation.
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