code: def __init__(
      self,
      name: str,
      dataset,
      record_class: Union[
          TokenClassificationRecord,
          Text2TextRecord,
          TextClassificationRecord,
      ],
      workspace: Optional[str] = None,
      multi_label: bool = False,
      settings: Union[
          TextClassificationSettings, TokenClassificationSettings
      ] = None,
      model: str = None,
      seed: int = None,
      *arg,
      **kwargs,
  ):
      self._name = name
      self._workspace = workspace or get_workspace()
      self._dataset = dataset
      self._record_class = record_class
      self._multi_label = multi_label
      self._settings = settings
      if self._settings:
          self._label2id = self._settings.label2id or None
          self._id2label = self._settings.id2label
          self._label_list = list(self._label2id.keys())
      else:
          self._label_list = None
          self._label2id = None
          self._id2label = None
      self._model = model
      self._seed = seed
      self.model_kwargs = {}
      self.trainer_kwargs = {}
      self.trainer_model = None
      self.trainer_tokenizer = None
      self._trainer = None
  
imports: import logging
  import os
  import warnings
  from abc import ABC, abstractmethod
  from typing import TYPE_CHECKING, Any, Dict, List, Optional, Union
  from argilla.client.datasets import DatasetForText2Text, DatasetForTextClassification, DatasetForTokenClassification
  from argilla.client.models import Framework, Text2TextRecord, TextClassificationRecord, TokenClassificationRecord
  from argilla.client.singleton import active_client
  from argilla.datasets import TextClassificationSettings, TokenClassificationSettings, load_dataset_settings
  from argilla.utils.telemetry import get_telemetry_client
label_desc: Use image node_id 1 to create a new ArgillaTrainerSkeleton object from inherited base classes: ABC with example: obj = ArgillaTrainerSkeleton(name, dataset, record_class, workspace, multi_label, settings, model, seed)