code: def query(model_w_task):
      model, task = model_w_task
      angle_bracket_mask_models = [
          "roberta",
          "camembert",
          "esm",
          "ibert",
          "luke",
          "mpnet",
          "yoso",
          "mpnet",
      ]
  
      if task == "fill-mask":
          if any(map(lambda x: x in model, angle_bracket_mask_models)):
              return "Hello I'm a <mask> model."
          else:
              return "Hell I'm a [MASK] model."
      elif task == "question-answering":
          return {
              "question": "What's my name?",
              "context": "My name is Clara and I live in Berkeley",
          }
      elif task == "text-classification":
          return "DeepSpeed is the greatest"
      elif task == "token-classification":
          return "My name is jean-baptiste and I live in montreal."
      elif task == "text-generation":
          return "DeepSpeed is the greatest"
      elif task == "text2text-generation":
          return "Is this review positive or negative? Review: this is the best cast iron skillet you will ever buy"
      elif task == "translation" or task == "summarization":
          return "Hello, my dog is cute"
      else:
          NotImplementedError(
              f'query for task "{task}" is not implemented'
          )
  
imports: import os
  import time
  import torch
  import pytest
  import itertools
  import deepspeed
  from deepspeed.git_version_info import torch_info
  from unit.common import DistributedTest
  from packaging import version
  from deepspeed.ops.op_builder import OpBuilder
  from transformers import pipeline, AutoTokenizer
  from transformers.models.t5.modeling_t5 import T5Block
  from transformers.models.roberta.modeling_roberta import RobertaLayer
  from huggingface_hub import HfApi
  from deepspeed.model_implementations import DeepSpeedTransformerInference
  from torch import nn
  from deepspeed.accelerator import get_accelerator
  from deepspeed.ops.op_builder import InferenceBuilder
label_desc: Use image node_id 6 for calling a global function with example usage: query(model_w_task) and returns: str, str, dict, str, str, str, str, str