code: def get_args():
      parser = ArgumentParser()
      parser.add_argument(
          "--in-file",
          type=str,
          default=None,
          required=True,
          help="Path to Huggingface LLaMA checkpoints",
      )
      parser.add_argument(
          "--out-file",
          type=str,
          default=None,
          required=True,
          help="Path to output .nemo file.",
      )
      parser.add_argument(
          "--tokenizer-model",
          type=str,
          default=None,
          required=False,
          help="Path to sentencepiece tokenizer model.",
      )
      parser.add_argument(
          "--precision", type=str, default="32", help="Model precision"
      )
      args = parser.parse_args()
      return args
  
file_path: NeMo/examples/multimodal/multimodal_llm/neva/convert_hf_llava_to_neva.py
imports: import os
  from argparse import ArgumentParser
  from collections import OrderedDict
  import torch
  from llava import LlavaLlamaForCausalLM
  from omegaconf import OmegaConf
  from pytorch_lightning.core.saving import _load_state
  from pytorch_lightning.trainer.trainer import Trainer
  from transformers import LlamaTokenizer
  from nemo.collections.multimodal.models.multimodal_llm.neva.neva_model import MegatronNevaModel
  from nemo.collections.nlp.parts.nlp_overrides import GradScaler, MegatronHalfPrecisionPlugin, NLPDDPStrategy, NLPSaveRestoreConnector, PipelineMixedPrecisionPlugin
  from nemo.utils import logging
label_desc: Use image node_id 1 for calling a global function with example usage: get_args() and returns: args