code: def __init__(self, model, name=None):
      self.model = model
      self.name = name if name != None else f"anonymous-fasttext"
      self.prediction_type = "embedder"
  
imports: import logging
  import multiprocessing
  import os
  from functools import partial
  import warnings
  import torch
  from torch.utils.data.sampler import SequentialSampler
  from tqdm import tqdm
  from typing import Generator, List, Union
  from farm.data_handler.dataloader import NamedDataLoader
  from farm.data_handler.processor import Processor, InferenceProcessor, NaturalQuestionsProcessor
  from farm.data_handler.utils import grouper
  from farm.data_handler.inputs import QAInput
  from farm.modeling.adaptive_model import AdaptiveModel, BaseAdaptiveModel, ONNXAdaptiveModel
  from farm.modeling.optimization import optimize_model
  from farm.utils import initialize_device_settings, MLFlowLogger
  from farm.utils import set_all_seeds, calc_chunksize, log_ascii_workers, Benchmarker
  from farm.modeling.predictions import QAPred
label_desc: Use image node_id 1 to create a new FasttextInferencer object  with example: obj = FasttextInferencer(model, name)