code: def decode(self, decoder_ids: List[int]) -> str:
      return self.tokenizer.decode(
          decoder_ids,
          skip_special_tokens=True,
          clean_up_tokenization_spaces=False,
      )
  
imports: import torch
  import time
  from dataclasses import dataclass
  from opentelemetry import trace
  from transformers import AutoTokenizer, AutoModelForSeq2SeqLM, PreTrainedTokenizerBase
  from typing import Optional, Tuple, List, Type, Dict
  from text_generation_server.utils.tokens import batch_top_tokens
  from text_generation_server.models import Model
  from text_generation_server.models.types import GeneratedText, Batch, Generation, Tokens
  from text_generation_server.pb import generate_pb2
  from text_generation_server.utils import NextTokenChooser, StoppingCriteria, Sampling
label_desc: Use image node_id 3 for calling the Seq2SeqLM obj's underlying member method code with example usage: obj.decode(decoder_ids) and returns: self