1 مستودع
Connecting router nodes so the output of one becomes the input of another, enabling complex model pipelines.
Distinct from Graph-Based Node Models: Distinct from Graph-Based Node Models: focuses on chaining inference nodes for model pipelines, not general graph data modeling.
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KServe is a Kubernetes-native platform for deploying and serving machine learning models as scalable inference services. It supports both generative AI models, including large language models, and traditional predictive models from frameworks such as TensorFlow, PyTorch, Scikit-Learn, XGBoost, and ONNX. The platform manages the full lifecycle of model deployments, including revision tracking, canary rollouts, A/B testing, and automatic rollbacks, and provides serverless scale-to-zero capabilities for cost-efficient resource management. KServe distinguishes itself through a standardized infere
Connects router nodes so the output of one becomes the input of another, enabling complex model pipelines.