Help Center/ PanguLargeModels/ User Guide/ Developing a Third-Party Model/ Deploying a Third-Party Model/ Creating a Third-Party Model Deployment Task
Updated on 2025-11-04 GMT+08:00
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Creating a Third-Party Model Deployment Task

The platform supports the deployment of trained models or preset models. The procedure is as follows:

  1. Log in to ModelArts Studio Large Model Deveopment Platform. In the My Spaces area, click the required workspace.
    Figure 1 My Spaces
  2. In the navigation pane, choose Model Development > Model Deployment. Click Create Deployment Task in the upper right corner.
  3. In the Select Model dialog box, set Sources to Model Square and Type to NLP, select a model, and click OK.
  4. On the Create Deployment Task page, set deployment parameters by referring to Table 1.
    Table 1 Parameters for deploying a third-party model

    Category

    Parameter

    Description

    Deployment Configuration

    Select Model

    You can modify the following information:

    • Sources: Select Model Square.
    • Type: Select NLP and select the model and version to be deployed.

    Deployment Mode

    Cloud-based deployment is supported. Deployment at the online: Algorithms are deployed in the resource pool provided by the platform.

    User Defined Name

    Unique identifier of the inference service when the inference service is called through the inference API of the V2 version. This configuration cannot be changed after file systems are created.

    Safety Fence

    Safety Fence

    Ensures the security of model calling.

    Version Selection

    Currently, only the basic edition of the security guardrail is supported, which is built-in with default content moderation rules.

    Resource Configuration

    Billing model

    Free for a limited time

    Instance Count

    Set the number of instances required for deploying the model.

    Subscription reminder

    Subscription reminder

    After this function is enabled, the system sends SMS or email notifications to users when the task status is updated.

    Basic information

    service name

    Set the name of the deployment task.

    Description (Optional)

    Set the description of the deployment task.

    Tag (Optional)

    Sets the tag of a deployment task. When deploying or updating a model, use SERVICE_TAGS_CONFIG as the key and the Base64 character string of the JSON body of the tag information as the value to add the tag to the environment variables of the model service.
  5. After setting the deployment parameters, click Deploy Now.