code: def __post_init__(self):
      super().__post_init__()
  
      self._visibility["output_directory"] = -1
  
      self._possible_values["llm_backbone"] = possible_values.String(
          values=(
              "h2oai/h2ogpt-4096-llama2-7b",
              "h2oai/h2ogpt-4096-llama2-7b-chat",
              "h2oai/h2ogpt-4096-llama2-13b",
              "h2oai/h2ogpt-4096-llama2-13b-chat",
              "h2oai/h2ogpt-4096-llama2-70b",
              "h2oai/h2ogpt-4096-llama2-70b-chat",
              "tiiuae/falcon-7b",
              "tiiuae/falcon-40b",
              "mistralai/Mistral-7B-v0.1",
              "HuggingFaceH4/zephyr-7b-beta",
              "stabilityai/stablelm-3b-4e1t",
              "facebook/opt-125m",
          ),
          allow_custom=True,
      )
  
imports: import os
  from dataclasses import dataclass, field
  from typing import Any, Dict, List, Tuple
  import llm_studio.src.datasets.text_causal_classification_ds
  import llm_studio.src.plots.text_causal_classification_modeling_plots
  from llm_studio.python_configs.base import DefaultConfig, DefaultConfigProblemBase
  from llm_studio.python_configs.text_causal_language_modeling_config import ConfigNLPAugmentation, ConfigNLPCausalLMArchitecture, ConfigNLPCausalLMDataset, ConfigNLPCausalLMEnvironment, ConfigNLPCausalLMLogging, ConfigNLPCausalLMTokenizer, ConfigNLPCausalLMTraining
  from llm_studio.src import possible_values
  from llm_studio.src.losses import text_causal_classification_modeling_losses
  from llm_studio.src.metrics import text_causal_classification_modeling_metrics
  from llm_studio.src.models import text_causal_classification_modeling_model
  from llm_studio.src.utils.modeling_utils import generate_experiment_name
label_desc: Use image node_id 1 for calling the ConfigProblemBase obj's underlying member method code with example usage: obj.__post_init__() without return types