code: def create_fixed_tokenizer(output_file):
      print("creating fixed tokenizer")
      import extra.junk.sentencepiece_model_pb2 as spb2
  
      mp = spb2.ModelProto()
      mp.ParseFromString(
          fetch(
              "https://huggingface.co/teknium/OpenHermes-2.5-Mistral-7B/resolve/main/tokenizer.model?download=true"
          ).read_bytes()
      )
      mp.pieces.append(
          spb2.ModelProto.SentencePiece(piece="<|im_end|>", score=0)
      )
      mp.pieces.append(
          spb2.ModelProto.SentencePiece(piece="<|im_start|>", score=0)
      )
      with open(output_file, "wb") as f:
          f.write(mp.SerializeToString())
  
imports: import os, sys, traceback
  from io import StringIO
  from contextlib import redirect_stdout
  from tinygrad import Tensor, nn, Device, dtypes
  from tinygrad.helpers import Timing, colored, getenv, fetch
  from extra.models.llama import Transformer, convert_from_huggingface
  from sentencepiece import SentencePieceProcessor
label_desc: Use image node_id 1 for calling a global function with example usage: create_fixed_tokenizer(output_file) without return types