code: def test_get_hf_task_for_model():
      model = "glaiveai/glaive-coder-7b"
      model_type = (
          litellm.llms.huggingface_restapi.get_hf_task_for_model(model)
      )
      print(f"model:{model}, model type: {model_type}")
      assert model_type == "text-generation-inference"
  
      model = "meta-llama/Llama-2-7b-hf"
      model_type = (
          litellm.llms.huggingface_restapi.get_hf_task_for_model(model)
      )
      print(f"model:{model}, model type: {model_type}")
      assert model_type == "text-generation-inference"
  
      model = "facebook/blenderbot-400M-distill"
      model_type = (
          litellm.llms.huggingface_restapi.get_hf_task_for_model(model)
      )
      print(f"model:{model}, model type: {model_type}")
      assert model_type == "conversational"
  
      model = "facebook/blenderbot-3B"
      model_type = (
          litellm.llms.huggingface_restapi.get_hf_task_for_model(model)
      )
      print(f"model:{model}, model type: {model_type}")
      assert model_type == "conversational"
  
      # neither Conv or None
      model = "roneneldan/TinyStories-3M"
      model_type = (
          litellm.llms.huggingface_restapi.get_hf_task_for_model(model)
      )
      print(f"model:{model}, model type: {model_type}")
      assert model_type == None
  
imports: import sys, os
  import traceback
  from dotenv import load_dotenv
  import os, io
  import pytest
  import litellm
  from litellm import embedding, completion, completion_cost, Timeout
  from litellm import RateLimitError
  import openai
label_desc: Use image node_id 12 for calling a global function with example usage: test_get_hf_task_for_model() without return types