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Deploying models directly from the Hugging Face Hub with native support and streamlined configuration.
Distinct from Hugging Face: Distinct from Hugging Face model conversion: focuses on deploying models directly from the Hub, not converting them to other formats.
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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
Deploys models directly from the Hugging Face Hub with native support and streamlined configuration.