code: def describe(self, attribute: Optional[str] = None) -> pd.DataFrame:
      args = self.model_storage.json_get("args")
      if attribute == "args":
          return pd.DataFrame(args.items(), columns=["key", "value"])
      elif attribute == "metadata":
          hf_api = HfApi()
          metadata = hf_api.model_info(args["model_name"])
          data = metadata.__dict__
          return pd.DataFrame(
              list(data.items()), columns=["key", "value"]
          )
      else:
          tables = ["args", "metadata"]
          return pd.DataFrame(tables, columns=["tables"])
  
file_path: mindsdb/mindsdb/integrations/handlers/huggingface_handler/huggingface_handler.py
imports: from typing import Dict, Optional
  import pandas
  import transformers
  from huggingface_hub import HfApi
  from mindsdb.integrations.handlers.huggingface_handler.settings import FINETUNE_MAP
  from mindsdb.integrations.libs.base import BaseMLEngine
  from mindsdb.utilities import log
label_desc: Use image node_id 10 for calling the HuggingFaceHandler obj's underlying member method code with example usage: obj.describe(attribute) and returns: pd, pd, pd