class_docstr: High-level Python wrapper for a bloom.cpp model.
code: def _supported_call(
      self,
      prompt: str,
      max_tokens: int,
      stream: bool = False,
      stop: Optional[List[str]] = [],
      echo: bool = False,
      model: Optional[str] = None,
      *args,
  ):
      # Check unsupporeted parameters
      unsupported_arg = [
          "suffix",
          "temperature",
          "top_p",
          "logprobs",
          "frequency_penalty",
          "presence_penalty",
          "repeat_penalty",
          "top_k",
          "tfs_z",
          "mirostat_mode",
          "mirostat_tau",
          "mirostat_eta",
          "model",
      ]
      defult_value = {
          "suffix": None,
          "temperature": 0.8,
          "top_p": 0.95,
          "logprobs": None,
          "frequency_penalty": 0.0,
          "presence_penalty": 0.0,
          "repeat_penalty": 1.1,
          "top_k": 40,
          "tfs_z": 1.0,
          "mirostat_mode": 0,
          "mirostat_tau": 5.0,
          "mirostat_eta": 0.1,
      }
      for index in range(len(args)):
          if args[index] != defult_value[unsupported_arg[index]]:
              warnings.warn(
                  f"The parameter {unsupported_arg[index]} is temporarily "
                  "unsupported, please use the default value."
              )
  
      if stream:
          return self.stream(prompt, max_tokens, stop, echo, model)
      else:
          return self._eval(
              prompt, max_tokens, False, stop, echo, model
          )
  
imports: from .bloom_cpp import bloom_load, bloom_free, bloom_run
  from .bloom_cpp import bloom_tokenize, bloom_detokenize, bloom_forward, bloom_eval, bloom_embed
  from bigdl.llm.utils.common import invalidInputError
  from bigdl.llm.ggml.model.generation import GenerationMixin
  from typing import List, Optional, Generator, Sequence, Union
  import time
  import uuid
  import warnings
label_desc: Use image node_id 3 for calling the Bloom obj's underlying member method code with example usage: obj._supported_call(prompt, max_tokens, stream, stop, echo, model) and returns: self, self