Models Overview

Models is used to register reusable models on the platform, including Preset models maintained by the platform and Custom models that you register. After registration, models can be referenced in Develop, Training, or Inference for model loading, fine-tuning, evaluation, or online deployment. Model management primarily records the location of model files, version, type, tags, description, and metadata, helping teams consistently find and reuse model assets.

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Applicable Scenarios

• Find platform-maintained public models and reference them in training or inference scenarios.
• Register training artifacts, proprietary models, or third-party models as models that can be referenced on the platform.
• Prepare model paths, versions, and metadata for inference services.

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Model Source

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Model Information

The model list and details typically include the following information:

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Usage Procedure

1. Select Preset or Custom based on the model source.
2. Find an existing model or register a new custom model.
3. Confirm the model name, version, storage path, and metadata.
4. Reference the model in development environments, training tasks, or inference services.

Models only registers the model asset itself. For inference service resource specifications, service access, scaling, and service operations and maintenance, see Create an LLM inference service, Manage LLM inference services, and Advanced inference service operations.

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Next Steps

• Use Preset Models
• Register and Manage Custom Models