code: def inf_kwargs(model_w_task):
      model, task = model_w_task
      if task == "text-generation":
          if model == "EleutherAI/gpt-j-6b":
              # This model on V100 is hitting memory problems that limit the number of output tokens
              return {
                  "do_sample": False,
                  "temperature": 1.0,
                  "max_length": 12,
              }
          return {
              "do_sample": False,
              "temperature": 1.0,
              "max_length": 20,
          }
      else:
          return {}
  
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 7 for calling a global function with example usage: inf_kwargs(model_w_task) and returns: dict, dict, dict