def load_masked_lm_model()

in optimum/exporters/executorch/tasks/masked_lm.py [0:0]

• 3 lines of code
• 4 McCabe index (conditional complexity)

def load_masked_lm_model(model_name_or_path: str, **kwargs) -> MaskedLMExportableModule:
    """
    Loads a seq2seq language model for conditional text generation and registers it under the task
    'fill-mask' using Hugging Face's `AutoModelForMaskedLM`.

    Args:
        model_name_or_path (str):
            Model ID on huggingface.co or path on disk to the model repository to export. For example:
            `model_name_or_path="google-bert/bert-base-uncased"` or `mode_name_or_path="/path/to/model_folder`
        **kwargs:
            Additional configuration options for the model.

    Returns:
        MaskedLMExportableModule:
            An instance of `MaskedLMExportableModule` for exporting and lowering to ExecuTorch.
    """

    eager_model = AutoModelForMaskedLM.from_pretrained(model_name_or_path, **kwargs).to("cpu").eval()
    return MaskedLMExportableModule(eager_model)