class_docstr: Base class for encoder decoder RNNT-based models.
class_docstr_tok: ["Base","class","for","encoder","decoder","RNNT-based","models","."]
docstr: This method returns a list of pre-trained model which can be instantiated directly from NVIDIA's NGC cloud.
  
  Returns:
      List of available pre-trained models.
docstr_tok: ["This","method","returns","a","list","of","pre-trained","model","which","can","be","instantiated","directly","from","NVIDIA","'s","NGC","cloud",".","Returns",":","List","of","available","pre-trained","models","."]
code: def list_available_models(cls) -> List[PretrainedModelInfo]:
      """
      This method returns a list of pre-trained model which can be instantiated directly from NVIDIA's NGC cloud.
  
      Returns:
          List of available pre-trained models.
      """
      results = []
  
      model = PretrainedModelInfo(
          pretrained_model_name="stt_zh_conformer_transducer_large",
          description="For details about this model, please visit https://catalog.ngc.nvidia.com/orgs/nvidia/teams/nemo/models/stt_zh_conformer_transducer_large",
          location="https://api.ngc.nvidia.com/v2/models/nvidia/nemo/stt_zh_conformer_transducer_large/versions/1.8.0/files/stt_zh_conformer_transducer_large.nemo",
      )
      results.append(model)
  
      return results
  
imports: import copy
  import json
  import os
  import tempfile
  from math import ceil
  from typing import Dict, List, Optional, Tuple, Union
  import torch
  from omegaconf import DictConfig, OmegaConf, open_dict
  from pytorch_lightning import Trainer
  from tqdm.auto import tqdm
  from nemo.collections.asr.data import audio_to_text_dataset
  from nemo.collections.asr.data.audio_to_text_dali import AudioToCharDALIDataset, DALIOutputs
  from nemo.collections.asr.data.audio_to_text_lhotse import LhotseSpeechToTextBpeDataset
  from nemo.collections.asr.losses.rnnt import RNNTLoss, resolve_rnnt_default_loss_name
  from nemo.collections.asr.metrics.wer import WER
  from nemo.collections.asr.models.asr_model import ASRModel, ExportableEncDecModel
  from nemo.collections.asr.modules.rnnt import RNNTDecoderJoint
  from nemo.collections.asr.parts.mixins import ASRModuleMixin
  from nemo.collections.asr.parts.submodules.rnnt_decoding import RNNTDecoding, RNNTDecodingConfig
  from nemo.collections.asr.parts.utils.audio_utils import ChannelSelectorType
  from nemo.collections.common.data.lhotse import get_lhotse_dataloader_from_config
  from nemo.collections.common.parts.preprocessing.parsers import make_parser
  from nemo.core.classes.common import PretrainedModelInfo, typecheck
  from nemo.core.classes.mixins import AccessMixin
  from nemo.core.neural_types import AcousticEncodedRepresentation, AudioSignal, LengthsType, NeuralType, SpectrogramType
  from nemo.utils import logging
label_desc: Use image node_id 26 for calling the EncDecRNNTModel obj's underlying member method code with example usage: obj.list_available_models(cls) and returns: results