class_docstr: Hugging Face LlamaForSequenceClassification.
  
  Llama is a multi-layer decoder-only Transformer. As such, the encoder
  is simply an identity layer. 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>.
  
  parlai em -m parlai.agents.hugging_face.llama:ParlaiLlamaClassifierAgent --classes __notok__ __ok__
code: def score(self, batch):
      return self.model(batch.text_vec)
  
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 5 for calling the ParlaiLlamaClassifierAgent obj's underlying member method code with example usage: obj.score(batch) and returns: self