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Model Serving Frameworks · Awesome GitHub Repositories

2 repos

Awesome GitHub RepositoriesModel Serving Frameworks

Platforms for hosting and serving machine learning models via APIs.

Distinguishing note: Focuses on the serving interface for multi-modal models.

Explore 2 awesome GitHub repositories matching artificial intelligence & ml · Model Serving Frameworks. Refine with filters or upvote what's useful.

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  • mudler/LocalAI

    mudler/LocalAI

    42,910View on GitHub↗

    LocalAI is a self-hosted inference server that enables the execution of machine learning models directly on local hardware. By providing a unified interface for text, image, and audio processing, it allows users to maintain full control over data privacy and infrastructure costs while eliminating dependencies on external network services. The platform functions as an API gateway that mimics standard cloud-based artificial intelligence interfaces, allowing existing applications to integrate local models as drop-in replacements. It utilizes a container-based architecture to package runtimes and

    Serves machine learning models through a compatible interface that handles text, image, and audio requests while optimizing system performance.

    Goaiapiaudio-generation
    42,910View on GitHub↗
  • ray-project/ray

    ray-project/ray

    41,400View on GitHub↗

    Ray is a distributed computing framework designed to scale Python and Java applications across clusters by abstracting task scheduling and resource management. It functions as a resource-aware execution engine that manages task dependencies, placement, and fault tolerance across networked compute nodes. At its core, the system provides a stateful actor model, allowing developers to define classes that run in dedicated processes to maintain and mutate internal state across remote method calls. The framework distinguishes itself through a robust cross-language interoperability layer, enabling f

    Deploying and scaling complex model pipelines across multiple GPUs to handle high-throughput requests with automatic resource autoscaling.

    Pythondata-sciencedeep-learningdeployment
    41,400View on GitHub↗