models.get_model

The get_model function provides a way to quickly download a prebuilt model for easy testing of leap-ie.

preprocessing_fn, model, class_list = get_model(
  model_name,
  source="source_name",
  segmentation=False,
)

Arguments

• model_name (str): Name of a Torchvision, Keras or HuggingFace model. When source is "keras" should be of the form module_name.model_name.

  • Required: Yes

  • Default: None

• source ("torchvision" | "keras" | "huggingface"): Name of a source repository to fetch the model from. Note: For "huggingface" source, only PyTorch models are supported.

  • Required: No

  • Default: "torchvision"

• segmentation (bool): Whether the fetched model should be a segmentation or classification model.

  • Required: No

  • Default: False

Returns

• preprocessing_fn

  • The preprocessing function used on inputs for inference.

• model

  • The model.

• class_list

  • List of class names corresponding to the model's output classes.

Examples

• Torchvision:get_model('resnet18', source='torchvision')

• Hugging Face: get_model('nateraw/vit-age-classifier', source='huggingface')

• Keras: get_model('resnet50.ResNet50', source='keras')