code: def replace_hf_weights(weights_file, input_hf_path, output_hf_path):
      model = AutoModelForCausalLM.from_pretrained(
          input_hf_path, local_files_only=True
      )
      nemo_exported = torch.load(weights_file)
  
      model.load_state_dict(nemo_exported)
      model.save_pretrained(output_hf_path)
      logging.info(f"Full HF model saved to {output_hf_path}")
  
file_path: NeMo/scripts/nlp_language_modeling/convert_nemo_falcon_to_hf.py
imports: import os
  from argparse import ArgumentParser
  from collections import OrderedDict
  import torch
  from pytorch_lightning import Trainer
  from transformers import AutoModelForCausalLM
  from nemo.collections.nlp.models.language_modeling.megatron_gpt_model import MegatronGPTModel
  from nemo.collections.nlp.parts.nlp_overrides import NLPDDPStrategy
  from nemo.collections.nlp.parts.utils_funcs import torch_dtype_from_precision
  from nemo.utils import logging
label_desc: Use image node_id 3 for calling a global function with example usage: replace_hf_weights(weights_file, input_hf_path, output_hf_path) without return types