code: def run_tokenizer1(prompt):
      from transformers import AutoTokenizer
  
      t = AutoTokenizer.from_pretrained("distilgpt2")
      llm_tokenizer = AutoTokenizer.from_pretrained(
          "h2oai/h2ogpt-oig-oasst1-512-6_9b"
      )
  
      from InstructorEmbedding import INSTRUCTOR
  
      emb = INSTRUCTOR("hkunlp/instructor-large")
  
      t0 = time.time()
      a = len(regTokenize(prompt))
      print("Regexp Tokenizer", a, time.time() - t0)
  
      t0 = time.time()
      a = len(nltkTokenize(prompt))
      print("NLTK Tokenizer", a, time.time() - t0)
  
      t0 = time.time()
      a = len(t(prompt)["input_ids"])
      print("Slow Tokenizer", a, time.time() - t0)
  
      t0 = time.time()
      a = len(llm_tokenizer(prompt)["input_ids"])
      print("Fast Tokenizer LLM", a, time.time() - t0)
  
      t0 = time.time()
      a = emb.tokenize([prompt])["input_ids"].shape[1]
      print("Instruct Embedding", a, time.time() - t0)
  
file_path: h2ogpt/tests/test_tokenizer.py
imports: import os
  import nltk
  import pytest
  from tests.utils import wrap_test_forked
  import re
  import time
label_desc: Use image node_id 4 for calling a global function with example usage: run_tokenizer1(prompt) without return types