class_docstr: Wrapper around the BigDL-LLM Transformer-INT4 model
  
  Example:
      .. code-block:: python
  
          from langchain.llms import TransformersLLM
          llm = TransformersLLM.from_model_id(model_id="THUDM/chatglm-6b")
class_docstr_tok: ["Wrapper","around","the","BigDL-LLM","Transformer-INT4","model","Example",":","..","code-block",":",":","python","from","langchain.llms","import","TransformersLLM","llm","=","TransformersLLM.from_model_id","(","model_id=","''","THUDM\/chatglm-6b","''",")"]
docstr: Get the identifying parameters.
docstr_tok: ["Get","the","identifying","parameters","."]
code: def _identifying_params(self) -> Mapping[str, Any]:
      """Get the identifying parameters."""
      return {
          "model_id": self.model_id,
          "model_kwargs": self.model_kwargs,
      }
  
file_path: BigDL/python/llm/src/bigdl/llm/langchain/llms/transformersllm.py
imports: import importlib.util
  import logging
  from typing import Any, List, Mapping, Optional
  from pydantic import Extra
  from langchain.callbacks.manager import CallbackManagerForLLMRun
  from langchain.llms.base import LLM
  from langchain.llms.utils import enforce_stop_tokens
label_desc: Use image node_id 3 for calling the TransformersLLM obj's underlying member method code with example usage: obj._identifying_params() and returns: dict