DeploymentName 联机部署的名称。 协议 请求的协议。 ResponseCode 返回到客户端的最终响应代码。 ResponseCodeReason 返回到客户端的最终响应代码原因。 ModelStatusCode 模型的响应状态代码。 ModelStatusReason 模型的响应状态原因。 RequestPayloadSize 从客户端接收的总字节数。 ResponsePayloadSize 发回客户端的总字节数...
POST jobs HTTP/1.1 Host: <ENDPOINT_URI> Authorization: Bearer <TOKEN> Content-Type: application/json azureml-model-deployment: DEPLOYMENT_NAME 配置作业属性 可以在调用时配置已创建的作业中的一些属性。 备注 配置作业属性的功能目前仅在包含管道组件部署的批处理终结点中可用。 配置试验名称 使用以下过程配...
deploymentName String 推理终结点部署名称。 cancellationToken CancellationToken 要使用的取消标记。 返回 Response<MachineLearningOnlineDeploymentResource> 例外 ArgumentException deploymentName是一个空字符串,预期为非空。 ArgumentNullException deploymentName为 null。
model, deployment_namestring要使用的语言模型。 如果将模型部署到无服务器 API 终结点,则不需要此参数。是* max_tokensinteger要在响应中生成的最大令牌数。 默认为 inf。否 温度FLOAT所生成文本的随机性。 默认值为 1。否 stoplist所生成文本的停止序列。 默认值为 null。否 ...
An Azure machine learning service for building and deploying models. 3,023 questions 1 answer Online Endpoint Deployment in Azure ML Studio I was using the Azure Machine learning studio yesterday and my endpoints were deployed perfectly. I came back today and I am unable to test my endpoints be...
az ml online-endpoint create--local-n$ENDPOINT_NAME-fendpoints/online/managed/sample/endpoint.yml 现在,在终结点下面创建一个名为blue的部署。 Azure CLI Python SDK 工作室 ARM 模板 Azure CLI az ml online-deployment create--local-nblue--endpoint$ENDPOINT_NAME-fendpoints/online/managed/sample/blue-...
An Azure machine learning service for building and deploying models. 2,833 questions askedAug 24, 2024, 5:29 AM Matias Larsson50Reputation points commentedSep 8, 2024, 12:06 PM Andy Lee0Reputation points 1 answer Can't run real-time deployment for best model in Azure ML: Resource provider...
Figure 8 The Azure Machine Learning Studio Action Pane When the Web service deployment completes, you’ll be redirected to the Web service dashboard, shown in Figure 9. The dash-board presents a summary of the published Web service, along with the API key and instructions on how to send re...
aciconfig = AciWebservice.deploy_configuration(cpu_cores=1,memory_gb=1,tags={"data":"Salary","method":"sklearn"},description='Predict Stackoverflow Salary')service = Webservice.deploy_from_model(workspace=ws,name='salary-svc',deployment_config=aciconfig,models=[model],image_config=image_config...
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