code: def get_model_tokenizer_gpt4all(
      base_model,
      n_jobs=None,
      gpu_id=None,
      n_gpus=None,
      max_seq_len=None,
      llamacpp_dict=None,
      llamacpp_path=None,
  ):
      cvd = os.getenv("CUDA_VISIBLE_DEVICES")
      if gpu_id is not None and gpu_id != -1:
          os.environ["CUDA_VISIBLE_DEVICES"] = str(gpu_id)
      assert llamacpp_dict is not None
      # defaults (some of these are generation parameters, so need to be passed in at generation time)
      model_name = base_model.lower()
      llama_kwargs = dict(
          model_name=model_name,
          model=None,
          n_jobs=n_jobs,
          n_gpus=n_gpus,
          main_gpu=gpu_id if gpu_id not in [None, -1, "-1"] else 0,
          inner_class=True,
          max_seq_len=max_seq_len,
          llamacpp_dict=llamacpp_dict,
          llamacpp_path=llamacpp_path,
      )
      model, tokenizer, redo, max_seq_len = get_llm_gpt4all(
          **llama_kwargs
      )
      if redo:
          del model
          del tokenizer
          clear_torch_cache()
          # auto max_seq_len
          llama_kwargs.update(dict(max_seq_len=max_seq_len))
          model, tokenizer, redo, max_seq_len = get_llm_gpt4all(
              **llama_kwargs
          )
      if cvd is not None:
          os.environ["CUDA_VISIBLE_DEVICES"] = cvd
      else:
          os.environ.pop("CUDA_VISIBLE_DEVICES", None)
      return model, tokenizer, "cpu" if n_gpus != 0 else "cuda"
  
imports: import inspect
  import os
  from typing import Dict, Any, Optional, List, Iterator
  from langchain.callbacks.manager import CallbackManagerForLLMRun
  from langchain.schema.output import GenerationChunk
  from langchain.llms import gpt4all
  from pydantic.v1 import root_validator
  from utils import FakeTokenizer, url_alive, download_simple, clear_torch_cache, n_gpus_global
  from langchain.callbacks.streaming_stdout import StreamingStdOutCallbackHandler
  from langchain.llms import LlamaCpp
label_desc: Use image node_id 1 for calling a global function with example usage: get_model_tokenizer_gpt4all(base_model, n_jobs, gpu_id, n_gpus, max_seq_len, llamacpp_dict, llamacpp_path) and returns: model,  tokenizer,  unknown