code: def from_pretrained(
      model_name="unsloth/mistral-7b-bnb-4bit",
      max_seq_length=4096,
      dtype=None,
      load_in_4bit=True,
      token=None,
      device_map="sequential",
      rope_scaling=None,
      fix_tokenizer=True,
      *args,
      **kwargs,
  ):
      if not SUPPORTS_FOURBIT and model_name in FOURBIT_MAPPER:
          model_name = FOURBIT_MAPPER[model_name]
          logger.warning_once(
              f"Unsloth: Your transformers version of {transformers_version} does not support native "
              f"4bit loading.\nThe minimum required version is 4.37.\n"
              f'Try `pip install "git+https://github.com/huggingface/transformers.git"`\n'
              f"to obtain the latest transformers build, then restart this session.\n"
              f"For now, we shall load `{model_name}` instead (still 4bit, just slower downloading)."
          )
      elif not load_in_4bit and model_name in FOURBIT_MAPPER:
          new_model_name = FOURBIT_MAPPER[model_name]
          logger.warning_once(
              f"Unsloth: You passed in `{model_name}` which is a 4bit model, yet you set\n"
              f"`load_in_4bit = False`. We shall load `{new_model_name}` instead."
          )
          model_name = new_model_name
      pass
  
      model_config = AutoConfig.from_pretrained(model_name)
      model_type = model_config.model_type
  
      if model_type == "llama":
          dispatch_model = FastLlamaModel
      elif model_type == "mistral":
          dispatch_model = FastMistralModel
      else:
          raise NotImplementedError(
              f"Unsloth: {model_name} not supported yet!\n"
              "Make an issue to https://github.com/unslothai/unsloth!",
          )
  
      return dispatch_model.from_pretrained(
          model_name=model_name,
          max_seq_length=max_seq_length,
          dtype=dtype,
          load_in_4bit=load_in_4bit,
          token=token,
          device_map=device_map,
          rope_scaling=rope_scaling,
          fix_tokenizer=fix_tokenizer,
          *args,
          **kwargs,
      )
  
imports: from .llama import FastLlamaModel, logger
  from .mistral import FastMistralModel
  from transformers import AutoConfig
  from transformers import __version__
label_desc: Use image node_id 1 for calling the FastLanguageModel obj's underlying member method code with example usage: obj.from_pretrained(model_name, max_seq_length, dtype, load_in_4bit, token, device_map, rope_scaling, fix_tokenizer) and returns: dispatch_model