code: def list_available_models(cls) -> "List[PretrainedModelInfo]":
      list_of_models = []
      model = PretrainedModelInfo(
          pretrained_model_name="tts_en_lj_vits",
          location="https://api.ngc.nvidia.com/v2/models/nvidia/nemo/tts_en_lj_vits/versions/1.13.0/files/vits_ljspeech_fp16_full.nemo",
          description="This model is trained on LJSpeech audio sampled at 22050Hz. This model has been tested on generating female English "
          "voices with an American accent.",
          class_=cls,
      )
      list_of_models.append(model)
      model = PretrainedModelInfo(
          pretrained_model_name="tts_en_hifitts_vits",
          location="https://api.ngc.nvidia.com/v2/models/nvidia/nemo/tts_en_hifitts_vits/versions/r1.15.0/files/vits_en_hifitts.nemo",
          description="This model is trained on HiFITTS sampled at 44100Hz with and can be used to generate male and female English voices with an American accent.",
          class_=cls,
      )
      list_of_models.append(model)
      return list_of_models
  
imports: import contextlib
  import omegaconf
  import torch
  from hydra.utils import instantiate
  from omegaconf import DictConfig, OmegaConf
  from pytorch_lightning import Trainer
  from pytorch_lightning.loggers import WandbLogger
  from torch.cuda.amp import autocast
  from torch.nn import functional
  from nemo.collections.tts.data.dataset import DistributedBucketSampler
  from nemo.collections.tts.losses.vits_losses import DiscriminatorLoss, FeatureMatchingLoss, GeneratorLoss, KlLoss
  from nemo.collections.tts.models.base import TextToWaveform
  from nemo.collections.tts.modules.vits_modules import MultiPeriodDiscriminator
  from nemo.collections.tts.parts.utils.helpers import clip_grad_value_, g2p_backward_compatible_support, plot_spectrogram_to_numpy, slice_segments
  from nemo.collections.tts.torch.tts_data_types import SpeakerID
  from nemo.core.classes.common import PretrainedModelInfo, typecheck
  from nemo.core.neural_types.elements import AudioSignal, FloatType, Index, IntType, TokenIndex
  from nemo.core.neural_types.neural_type import NeuralType
  from nemo.core.optim.lr_scheduler import CosineAnnealing
  from nemo.utils import logging, model_utils
  from nemo.utils.decorators.experimental import experimental
label_desc: Use image node_id 14 for calling the VitsModel obj's underlying member method code with example usage: obj.list_available_models(cls) and returns: list_of_models