code: def gpt2_124M():
      cfg = CN()
      # Config for the roberta base model
      cfg.MODEL = CN()
      cfg.MODEL.vocab_size = 50257
      cfg.MODEL.units = 768
      cfg.MODEL.max_length = 1024
      cfg.MODEL.num_heads = 12
      cfg.MODEL.num_layers = 12
      cfg.MODEL.embed_dropout_prob = 0.1
      cfg.MODEL.hidden_dropout_prob = 0.1
      cfg.MODEL.attention_dropout_prob = 0.1
      cfg.MODEL.pos_embed_type = "learned"
      cfg.MODEL.activation = "gelu(tanh)"
      cfg.MODEL.layer_norm_eps = 1e-5
      cfg.MODEL.dtype = "float32"
      # Layout
      cfg.MODEL.layout = "NT"
      cfg.MODEL.compute_layout = "auto"
      # Initialization method
      cfg.INITIALIZER = CN()
      cfg.INITIALIZER.embed = ["truncnorm", 0, 0.02]
      cfg.INITIALIZER.weight = ["truncnorm", 0, 0.02]
      cfg.INITIALIZER.bias = ["zeros"]
      cfg.VERSION = 1
      cfg.freeze()
      return cfg
  
imports: import os
  from typing import Tuple
  import mxnet
  from mxnet import use_np, np, npx
  from mxnet.gluon import HybridBlock, nn
  from .base import BACKBONE_REGISTRY
  from ..base import get_model_zoo_home_dir, get_repo_model_zoo_url, get_model_zoo_checksum_dir
  from ..utils.config import CfgNode
  from ..utils.misc import load_checksum_stats, download
  from ..utils.registry import Registry
  from ..initializer import TruncNorm
  from ..attention_cell import MultiHeadAttentionCell
  from ..layers import get_activation, PositionalEmbedding
  from ..data.tokenizers import HuggingFaceByteBPETokenizer
label_desc: Use image node_id 1 for calling a global function with example usage: gpt2_124M() and returns: cfg