def __init__(self, **kwargs: Any) -> None:
        """
        Initialize.

        Args:
            kwargs: See the class-level Fields.

        """
        if kwargs.get("model_name") is None:
            task = kwargs.get("task", "")
            # NOTE: task being None or empty string leads to ValueError,
            # which ensures model is present
            kwargs["model_name"] = InferenceClient.get_recommended_model(task=task)
            logger.debug(
                f"Using Hugging Face's recommended model {kwargs['model_name']}"
                f" given task {task}."
            )
            print(kwargs["model_name"], flush=True)
        super().__init__(**kwargs)  # Populate pydantic Fields
        self._sync_client = InferenceClient(**self._get_inference_client_kwargs())
        self._async_client = AsyncInferenceClient(**self._get_inference_client_kwargs())
        self._get_model_info = model_info

        Initialize.

        Args:
            kwargs: See the class-level Fields.

        
llama-index-integrations/embeddings/llama-index-embeddings-huggingface-api/llama_index/embeddings/huggingface_api/base.py