import fasttext.util class PreTrainedPipeline(): def __init__(self, path=""): """ Initialize model """ self.model = fasttext.load_model(os.path.join(path, 'cc.en.300.bin')) def __call__(self, inputs: str) -> List[float]: """ Args: inputs (:obj:`str`): a string to get the features of. Return: A :obj:`list` of floats: The features computed by the model. """ return self.model.get_sentence_vector(inputs)