# Get Model by ID

Retrieve full model information including name, description, status (Created/InProgress/Completed/Failed/Stopping/Stopped), training version (Light/Max), generation prefix, project ID, dataset ID, and timestamps.

Endpoint: GET /tailored-gen/models/{model_id}

## Path parameters:

  - `model_id` (integer, required)
    Model ID

## Header parameters:

  - `api_token` (string, required)

## Response 200 fields (application/json):

  - `id` (integer)
    Unique identifier for the model

  - `name` (string)
    Name of the model

  - `description` (string)
    Description of the model

  - `status` (string)
    Status of the model
    Enum: "Created", "InProgress", "Completed", "Failed", "Stopping", "Stopped"

  - `training_mode` (string)
    Training configuration strategy
    Enum: "fully_automated", "expert"

  - `training_version` (string)
    Training version
    Enum: "light", "max", "bria-2.3", "bria-3.2"

  - `active_model_version` (string)
    The active version (checkpoint) of the model. becomes relevant after a training has been completed.

  - `training_parameters` (object)
    The training parameters used for the model. will be filled using the /start_training endpoint.

  - `checkpoint_steps` (array)
    A list of checkpoints saved for the model. will be filled using the /start_training endpoint.

  - `generation_prefix` (string)
    Text drawn from the dataset's caption_prefix that is automatically prepended to generation prompts to maintain consistency. It matches the dataset's caption_prefix. It can be bypassed during generation by setting include_generation_prefix=false.

  - `project_id` (integer)
    ID of the project this model belongs to

  - `dataset_id` (integer)
    ID of the dataset used for training

  - `created_at` (string)
    Timestamp when the model was created