TFServing3 Kubeflow 1.0 기능 #5 (KFServing, TFServing) 2020.03.13 1. Model serving overview - https://v1-0-branch.kubeflow.org/docs/reference/pytorchjob/v1/pytorch/ - Kubeflow supports two model serving systems that allow multi-framework model serving: KFServing and Seldon Core. Alternatively, you can use a standalone model serving system. a. Multi-framework model serving - A check mark (✓) indicates that the system (KFServing or Seldon Core) suppor.. 2021. 9. 25. Kubeflow 1.0 기능 #2 (TF-Job, TF-Serving, Kubeflow pipeline) 2020.02.26 1. 개요 - GKE에 설치한 Kubeflow의 Pipeline 기능을 이해하기 위해 아래 사이트를 참조하여 사용 해 봄 - Using Kubeflow for Financial Time Series (https://github.com/kubeflow/examples/tree/master/financial_time_series) - This example covers the following concepts: a. Deploying Kubeflow to a GKE cluster b. Exploration via JupyterHub (prospect data, preprocess data, develop ML model) c. Training several tensorflow models.. 2021. 9. 24. Running the MNIST using distributed training 2021.5.28 1. Running the MNIST on-prem Jupyter notebook - The MNIST on-prem notebook builds a Docker image, launches a TFJob to train a model, and creates an InferenceService (KFServing) to deploy the trained model. - https://v1-2-branch.kubeflow.org/docs/started/workstation/minikube-linux/#running-the-mnist-on-prem-jupyter-notebook a. Prerequisites - Step 1: Set up Python environment in MacOS y.. 2021. 9. 24. 이전 1 다음
