code: def get_huggingface_pretrained_lm_models_list(
      include_external: bool = False,
  ) -> List[str]:
      """
      Returns the list of pretrained HuggingFace language models
  
      Args:
          include_external if true includes all HuggingFace model names, not only those supported language models in NeMo.
  
      Returns the list of HuggingFace models
      """
  
      huggingface_models = []
      for model in HUGGINGFACE_MODELS:
          model_names = HUGGINGFACE_MODELS[model][
              "pretrained_model_list"
          ]
          huggingface_models.extend(model_names)
      return huggingface_models
  
file_path: NeMo/nemo/collections/nlp/modules/common/huggingface/huggingface_utils.py
imports: import os
  from typing import List, Optional
  from transformers import ALBERT_PRETRAINED_MODEL_ARCHIVE_LIST, BERT_PRETRAINED_MODEL_ARCHIVE_LIST, CAMEMBERT_PRETRAINED_MODEL_ARCHIVE_LIST, DISTILBERT_PRETRAINED_MODEL_ARCHIVE_LIST, GPT2_PRETRAINED_MODEL_ARCHIVE_LIST, ROBERTA_PRETRAINED_MODEL_ARCHIVE_LIST, AlbertConfig, AutoModel, BertConfig, CamembertConfig, DistilBertConfig, GPT2Config, RobertaConfig
  from nemo.collections.nlp.modules.common.huggingface.albert import AlbertEncoder
  from nemo.collections.nlp.modules.common.huggingface.bert import BertEncoder
  from nemo.collections.nlp.modules.common.huggingface.camembert import CamembertEncoder
  from nemo.collections.nlp.modules.common.huggingface.distilbert import DistilBertEncoder
  from nemo.collections.nlp.modules.common.huggingface.gpt2 import GPT2Encoder
  from nemo.collections.nlp.modules.common.huggingface.roberta import RobertaEncoder
  from nemo.utils import logging
label_desc: Use image node_id 2 for calling a global function with example usage: get_huggingface_pretrained_lm_models_list(include_external) and returns: huggingface_models