def METHOD_NAME(self):
    conf = OmegaConf.load("conf/search_config/t5/41.2b.yaml")
    s = """
    train_settings:
      model_size_in_b: 41.2
      num_nodes: 40
      gpus_per_node: 8
      gpu_memory_gb: 80
      max_training_days: 85
      limit_search_runs: 100
      output_top_n: 10
      max_steps_per_run: 50
      max_minutes_per_run: 90
      tflops_per_gpu: 140
      num_tokens_in_b: 1000
      vocab_size: 29000
      seq_length: 512 # available seq_length list for T5 models: [512]
      custom_config: null # path to custom .yaml model config instead of using auto-generated
      logs: ${base_results_dir}/${search_config_value}_${.gpu_memory_gb}gb
      tensor_parallel_sizes: auto
      pipeline_parallel_sizes: auto
      min_model_parallel_size: auto  # auto to use our recommendation, or a value for the minimum desired parallelism
      max_model_parallel_size: auto  # auto to use our recommendation, or a value for the maximum desired parallelism
      micro_batch_sizes: auto
      act_ckpt_layers: auto