class_docstr: Hugging Face Llama Agent.
  
  LlamaForCausalLM is a multi-layer decoder-only Transformer.
  The decoder is initialized with pretrained weights from Hugging Face.
  Read more about this model here
  <https://huggingface.co/docs/transformers/main/model_doc/llama>.
code: def add_cmdline_args(
      cls, parser: ParlaiParser, partial_opt: Optional[Opt] = None
  ) -> ParlaiParser:
      super().add_cmdline_args(parser, partial_opt=partial_opt)
      group = parser.add_argument_group("LlamaAgent Args")
      group = setup_llama_args(group)
      return parser
  
imports: from typing import Optional
  from parlai.core.params import ParlaiParser
  from parlai.core.opt import Opt
  import torch
  from parlai.agents.hugging_face.dict import LlamaDictionaryAgent, _init_llama_path
  from parlai.core.torch_generator_agent import TorchGeneratorAgent, TorchGeneratorModel
  from parlai.core.torch_classifier_agent import TorchClassifierAgent
  from parlai.utils.torch import IdentityLayer, padded_tensor
  from parlai.agents.transformer.transformer import _check_positional_embeddings
  import parlai.utils.logging
label_desc: Use image node_id 1 for calling the LlamaAgent obj's underlying member method code with example usage: obj.add_cmdline_args(cls, parser, partial_opt) and returns: parser