code: def test_completion_hf_prompt_array():
      try:
          litellm.set_verbose = True
          print("\n testing hf mistral\n")
          response = text_completion(
              model="huggingface/mistralai/Mistral-7B-v0.1",
              prompt=token_prompt,  # token prompt is a 2d list,
              max_tokens=0,
              temperature=0.0,
              # echo=True, # hugging face inference api is currently raising errors for this, looks like they have a regression on their side
          )
          print("\n\n response")
  
          print(response)
          print(response.choices)
          assert len(response.choices) == 2
          # response_str = response["choices"][0]["text"]
      except Exception as e:
          print(str(e))
          if "is currently loading" in str(e):
              return
          pytest.fail(f"Error occurred: {e}")
  
file_path: litellm/litellm/tests/test_text_completion.py
imports: import sys, os, asyncio
  import traceback
  from dotenv import load_dotenv
  import os, io
  import pytest
  import litellm
  from litellm import embedding, completion, text_completion, completion_cost, atext_completion
  from litellm import RateLimitError
label_desc: Use image node_id 7 for calling a global function with example usage: test_completion_hf_prompt_array() without return types