code: def run_suite(
      model_args,
      suite,
      prompt,
      *,
      model_type="hf-causal",
      output=None,
      verbose=False,
      limit=None,
  ):
      # Confusing detail: in the "simple evaluate", "model" is the HF model type,
      # which is almost always hf-causal or hf-causal-experimental. `model_args`
      # looks like this:
      #
      #     pretrained=hoge/piyo,tokenizer=...,asdf=...
  
      # device never changes in practice
      device = "cuda"
  
      specs = load_suite(suite)
      tasks, num_fewshot = build_eval_args(specs, prompt)
  
      evaluator.simple_evaluate(
          model=model_type,
          model_args=model_args,
          tasks=tasks,
          num_fewshot=num_fewshot,
          device=device,
          verbose=verbose,
          limit=limit,
      )
  
imports: import argparse
  from lm_eval import evaluator
  from lm_eval.prompts import get_prompt_code
  from lm_eval.suites import TaskSpec, load_suite
label_desc: Use image node_id 2 for calling a global function with example usage: run_suite(model_args, suite, prompt) without return types