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 __init__(self, opt, shared=None):
      super().__init__(opt, shared)
      if hasattr(self.model, "module"):
          self.START_IDX = self.model.module.START_IDX
          self.END_IDX = self.model.module.END_IDX
          self.NULL_IDX = self.model.module.NULL_IDX
      else:
          self.START_IDX = self.model.START_IDX
          self.END_IDX = self.model.END_IDX
          self.NULL_IDX = self.model.NULL_IDX
  
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 2 to create a new LlamaAgent object from inherited base classes: TorchGeneratorAgent with example: obj = LlamaAgent(opt, shared)