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2 repositorios

Awesome GitHub RepositoriesMachine Learning Infrastructure Hosting

Deploys centralized servers to manage machine learning pipelines, track metadata, and enable team collaboration.

Distinct from Production Machine Learning: Distinct from Production Machine Learning: focuses on the hosting of the orchestration server itself rather than general production ML tools.

Explore 2 awesome GitHub repositories matching artificial intelligence & ml · Machine Learning Infrastructure Hosting. Refine with filters or upvote what's useful.

Awesome Machine Learning Infrastructure Hosting GitHub Repositories

Encuentra los mejores repositorios con IA.Buscaremos los repositorios que mejor coincidan usando IA.
  • zenml-io/zenmlAvatar de zenml-io

    zenml-io/zenml

    5,451Ver en GitHub↗

    ZenML is an orchestration platform designed for building, deploying, and monitoring reproducible machine learning pipelines and agentic workflows. It provides a unified framework that manages the entire lifecycle of machine learning assets, from data processing and model training to the deployment of persistent inference services. By decoupling pipeline logic from underlying compute and storage, the platform enables teams to transition workflows seamlessly from local development environments to production-grade cloud infrastructure. The platform distinguishes itself through a service-oriented

    Deploys a centralized server to manage machine learning pipelines, track metadata, and enable team collaboration across production-grade environments.

    Pythonagentopsagentsai
    Ver en GitHub↗5,451
  • huggingface/hub-docsAvatar de huggingface

    huggingface/hub-docs

    506Ver en GitHub↗

    This repository serves as the documentation source for the Hugging Face Hub, a collaborative platform designed for hosting, versioning, and discovering machine learning models, datasets, and interactive applications. It provides the foundational infrastructure for managing machine learning assets through Git-based repositories, which support large file storage, branching, and comprehensive commit history. The platform distinguishes itself by integrating metadata-driven discovery and structured management systems that allow users to attach licensing, task categories, and performance metrics to

    Hosts and serves pre-trained machine learning models with standardized metadata, documentation, and browser-based inference widgets.

    Handlebarshacktoberfestmachine-learning
    Ver en GitHub↗506
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  • Model Hosting PlatformsCentralized services for hosting, versioning, and serving pre-trained machine learning models with metadata and inference capabilities. **Distinct from Machine Learning Infrastructure Hosting:** Distinct from Machine Learning Infrastructure Hosting: focuses specifically on the model hosting and discovery aspect rather than general pipeline orchestration.