:original_name: modelarts_23_0098.html .. _modelarts_23_0098: Introduction to Model Templates =============================== Because the configurations of models with the same functions are similar, ModelArts integrates the configurations of such models into a common template. By using this template, you can easily and quickly import models without compiling the **config.json** configuration file. In simple terms, a template integrates AI engine and model configurations. Each template corresponds to a specific AI engine and inference mode. With the templates, you can quickly import models to ModelArts. Using a Template ---------------- The following uses the template described in as an example. Upload the TensorFlow model package to OBS before using the template. Store the model files in the **model** directory. When creating a model using this template, you need to select the **model** directory. #. On the **Import Model** page, set **Meta Model Source** to **Template**. #. In the **Template** area, select . ModelArts also provides three filter criteria: **Type**, **Engine**, and **Environment**, helping you quickly find the desired template. If the three filter criteria cannot meet your requirements, you can enter keywords to search for the target template. .. figure:: /_static/images/en-us_image_0000001278010777.png :alt: **Figure 1** Selecting a template **Figure 1** Selecting a template #. For **Model Folder**, select the **model** directory where the model files reside. For details, see :ref:`Template Description `. .. note:: If a training job is executed for multiple times, different version directories are generated, such as V001 and V002, and the generated models are stored in the **model** folder in different version directories. When selecting model files, specify the **model** folder in the corresponding version directory. #. If the default input and output mode of the selected template can be overwritten, you can select an input and output mode based on the model function or application scenario. **Input and Output Mode** is an abstract of the API in **config.json**. It describes the interface provided by the model for external inference. An input and output mode describes one or more APIs, and corresponds to a template. For details about the supported input and output modes, see :ref:`Input and Output Modes `. .. _modelarts_23_0098__en-us_topic_0172873520_section44801025155417: Supported Templates ------------------- - :ref:`TensorFlow-py27 General Template ` - :ref:`TensorFlow-py36 General Template ` - :ref:`MXNet-py27 General Template ` - :ref:`MXNet-py37 General Template ` - :ref:`PyTorch-py27 General Template ` - :ref:`PyTorch-py37 General Template ` - :ref:`Caffe-CPU-py27 General Template ` - :ref:`Caffe-GPU-py27 General Template ` - :ref:`Caffe-CPU-py37 General Template ` - :ref:`Caffe-CPU-py37 General Template ` .. _modelarts_23_0098__en-us_topic_0172873520_section737759781: Supported Input and Output Modes -------------------------------- - :ref:`Built-in Object Detection Mode ` - :ref:`Built-in Image Processing Mode ` - :ref:`Built-in Predictive Analytics Mode ` - :ref:`Undefined Mode `