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>.
docstr: Return the dictionary class that this agent expects to use.
  
  Can be overridden if a more complex dictionary is required.
docstr_tok: ["Return","the","dictionary","class","that","this","agent","expects","to","use",".","Can","be","overridden","if","a","more","complex","dictionary","is","required","."]
code: def dictionary_class():
      """
      Return the dictionary class that this agent expects to use.
  
      Can be overridden if a more complex dictionary is required.
      """
      return LlamaDictionaryAgent
  
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 3 for calling the LlamaAgent obj's underlying member method code with example usage: obj.dictionary_class() and returns: LlamaDictionaryAgent