code: def _llama2_13b() -> LLaMAConfig:
      return LLaMAConfig(
          model_dim=5120,
          max_seq_len=4096,
          vocab_info=VocabularyInfo(
              size=32000, unk_idx=0, bos_idx=1, eos_idx=2, pad_idx=None
          ),
          num_layers=40,
          num_attn_heads=40,
          num_key_value_heads=40,
          ffn_inner_dim=5120 * 4,
          ffn_inner_dim_to_multiple=256,
          dropout_p=0.1,
      )
  
imports: from dataclasses import dataclass
  from typing import Optional
  from fairseq2.data import VocabularyInfo
  from fairseq2.models.transformer import TransformerDecoderModel, TransformerEmbeddingFrontend, TransformerFrontend, init_final_projection
  from fairseq2.models.utils import ArchitectureRegistry
  from fairseq2.nn.embedding import StandardEmbedding
  from fairseq2.nn.lora import LoRAConfig
  from fairseq2.nn.normalization import LayerNorm, RMSNorm
  from fairseq2.nn.position_encoder import RotaryEncoder
  from fairseq2.nn.projection import Linear
  from fairseq2.nn.transformer import FeedForwardNetwork, GLUFeedForwardNetwork, MultiheadAttention, StandardMultiheadAttention, StandardTransformerDecoder, StandardTransformerDecoderLayer, TransformerDecoder, TransformerDecoderLayer, TransformerNormOrder, create_default_sdpa
  from fairseq2.typing import DataType, Device
label_desc: Use image node_id 6 for calling a global function with example usage: _llama2_13b() and returns: LLaMAConfig