code: def estimate_command(args):
      data = gather_data(args)
      for row in data:
          for i, item in enumerate(row):
              if isinstance(item, (int, float)):
                  row[i] = convert_bytes(item)
  
      headers = [
          "dtype",
          "Largest Layer",
          "Total Size",
          "Training using Adam",
      ]
  
      title = f"Memory Usage for loading `{args.model_name}`"
      table = create_ascii_table(headers, data, title)
      print(table)
  
file_path: accelerate/src/accelerate/commands/estimate.py
imports: import argparse
  from huggingface_hub import model_info
  from huggingface_hub.utils import GatedRepoError, RepositoryNotFoundError
  from accelerate import init_empty_weights
  from accelerate.utils import calculate_maximum_sizes, convert_bytes, is_timm_available, is_transformers_available
label_desc: Use image node_id 7 for calling a global function with example usage: estimate_command(args) without return types