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        • ModelArts Studio (MaaS) Usage - ModelArts

          ModelArts Studio (MaaS) Usage - ModelArts

          Step Operation Document 1 Making preparations Before using ModelArts Studio, create required resources, such as OBS buckets and resource pools.

          Help > ModelArts > ModelArts Studio (MaaS) User Guide
        • Managing Visualization Jobs - ModelArts

          Managing Visualization Jobs - ModelArts

          The OBS directory you use and ModelArts are in the same region. Creating a Visualization Job Log in to the ModelArts management console. In the left navigation pane, choose Training Jobs. On the displayed page, click the Visualization Jobs tab.

          Help > ModelArts > User Guide (Senior AI Engineers) > Training Management (Old Version )
        • Creating a Training Job Configuration - ModelArts

          Creating a Training Job Configuration - ModelArts

          By default, this parameter is left blank. inputs No String OBS storage path of a training job dataset_id No String Dataset ID of a training job.

          Help > ModelArts > SDK Reference > Training Management (Old Version) > Training Job Parameter Configuration
        • Upgrading a Service - ModelArts

          Upgrading a Service - ModelArts

          OBS Not supported Not supported Method 1: Modify Service Information on the Service Management Page Log in to the ModelArts management console and choose Service Deployment from the left navigation pane. Go to the service management page of the target service.

          Help > ModelArts > Model Inference (To Be Offline) > Deploying an AI Application as a Service
        • Scikit-learn - ModelArts

          Scikit-learn - ModelArts

          After the model is saved, it must be uploaded to the OBS directory before being published. The config.json and customize_service.py files must be contained during publishing. For details about the definition method, see Introduction to Model Package Specifications.

          Help > ModelArts > Model Inference (To Be Offline) > Inference Specifications > Examples of Custom Scripts
        • Assigning the Required Permissions - ModelArts

          Assigning the Required Permissions - ModelArts

          After the permission is granted, you can access OBS and SWR of IAM users in a notebook instance.

          Help > ModelArts > Best Practices > Permissions Management > Configuration Practices in Typical Scenarios
        • Searching for a Notebook Instance - ModelArts

          Searching for a Notebook Instance - ModelArts

          After the permission is granted, you can access OBS and SWR of IAM users in a notebook instance.

          Help > ModelArts > ModelArts User Guide (Standard) > Using Notebook for AI Development and Debugging > Managing Notebook Instances
        • Creating an Image Classification Project - ModelArts

          Creating an Image Classification Project - ModelArts

          Output Path Select an OBS path for storing ExeML data. NOTE: The output path stores all data generated in the ExeML project. Training Flavor Select a training flavor for this ExeML project. You will be billed based on different flavors.

          Help > ModelArts > ModelArts User Guide (Standard) > Using ExeML for Zero-Code AI Development > Using ExeML for Image Classification
        • Creating an Object Detection Project - ModelArts

          Creating an Object Detection Project - ModelArts

          Output Path An OBS path for storing ExeML data NOTE: The output path stores all data generated in the ExeML project. Training Flavor Select a training flavor for this ExeML project. You will be billed based on different flavors.

          Help > ModelArts > ModelArts User Guide (Standard) > Using ExeML for Zero-Code AI Development > Using ExeML for Object Detection
        • Creating a Sound Classification Project - ModelArts

          Creating a Sound Classification Project - ModelArts

          Output Path An OBS path for storing ExeML data NOTE: The output path stores all data generated in the ExeML project. Training Flavor Select a training flavor for this ExeML project. You will be billed based on different flavors.

          Help > ModelArts > ModelArts User Guide (Standard) > Using ExeML for Zero-Code AI Development > Using ExeML for Sound Classification
        • Creating a Text Classification Project - ModelArts

          Creating a Text Classification Project - ModelArts

          Output Path Select an OBS path for storing ExeML data. NOTE: The output path stores all data generated in the ExeML project. Training Flavor Select a training flavor for this ExeML project. You will be billed based on different flavors.

          Help > ModelArts > ModelArts User Guide (Standard) > Using ExeML for Zero-Code AI Development > Using ExeML for Text Classification
        • XGBoost - ModelArts

          XGBoost - ModelArts

          After the model is saved, it must be uploaded to the OBS directory before being published. The config.json configuration and the customize_service.py inference code must be included during the publishing.

          Help > ModelArts > Model Inference (To Be Offline) > Inference Specifications > Examples of Custom Scripts
        • Creating a Predictive Analytics Project - ModelArts

          Creating a Predictive Analytics Project - ModelArts

          Output Path Select an OBS path for storing ExeML data. NOTE: The output path stores all data generated in the ExeML project. Training Flavor Select a training flavor for this ExeML project. You will be billed based on different flavors.

          Help > ModelArts > ModelArts User Guide (Standard) > Using ExeML for Zero-Code AI Development > Using ExeML for Predictive Analytics
        • Labeling Text Classification Data - ModelArts

          Labeling Text Classification Data - ModelArts

          Figure 2 Data labeling - text classification Adding or Deleting Data In an ExeML project, the data source is the OBS directory corresponding to the input path of the dataset.

          Help > ModelArts > ModelArts User Guide (Standard) > Using ExeML for Zero-Code AI Development > Using ExeML for Text Classification
        • Querying the Status of a Dataset Export Task - ModelArts

          Querying the Status of a Dataset Export Task - ModelArts

          The options are as follows: DIR: Data is exported to OBS (default value).

          Help > ModelArts > API Reference > Historical APIs > Data Management (Old Version)
        • ma-cli image Commands for Building Images - ModelArts

          ma-cli image Commands for Building Images - ModelArts

          # Build a local image and save to local path and OBS ma-cli image build .ma/customize_from_ubuntu_18.04_to_modelarts/Dockerfile --target .

          Help > ModelArts > ModelArts User Guide (Standard) > Using Notebook for AI Development and Debugging > ModelArts CLI Command Reference
        • Accepting Team Labeling Results - ModelArts

          Accepting Team Labeling Results - ModelArts

          However, the original data in the dataset and the labeled data that has been accepted are still stored in the corresponding OBS bucket. Parent topic: Team Labeling

          Help > ModelArts > Data Labeling (To Be Offline) > Team Labeling
        • TensorFlow 2.1 - ModelArts

          TensorFlow 2.1 - ModelArts

          # Directories for storing the label.txt file on OBS and in the model package # with open(os.path.join(self.model_path, 'label.txt')) as f: # self.label = json.load(f) # Load the model in saved_model format in non-blocking mode to prevent blocking

          Help > ModelArts > Model Inference (To Be Offline) > Inference Specifications > Examples of Custom Scripts
        • Development Environment - ModelArts

          Development Environment - ModelArts

          Storage resource fee: fee for storing data in OBS, EVS, or SFS Table 1 Billing items Billing Item Description Billing Mode Billing Formula Compute resource Public resource pools Usage of compute resources. For details, see ModelArts Pricing Details.

          Help > ModelArts > Billing > Billing Item (ModelArts Standard)
        • Configuring Workflow Parameters - ModelArts

          Configuring Workflow Parameters - ModelArts

          Currently, obs, flavor, train_flavor, swr, and pacific are supported. No str delay Whether parameters are set when the workflow is running. The default value is False, indicating that parameters are set before the workflow runs.

          Help > ModelArts > ModelArts User Guide (Standard) > Using Workflows for Low-Code AI Development > Workflow Development Command Reference
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