class_docstr: High-level Python wrapper for a bloom.cpp model.
docstr: Create a generator of tokens from a prompt.
  
  Examples:
      >>> llm = Bloom(your_model_path)
      >>> tokens = llm._tokenize(b"Learning English is")
      >>> for token in llm._generate(tokens):
      >>>     print(llm.detokenize([token]).decode("utf-8", errors="ignore"))
  
  Args:
      tokens: The prompt tokens.
  
  Yields:
      The generated tokens.
docstr_tok: ["Create","a","generator","of","tokens","from","a","prompt",".","Examples",":",">",">",">","llm","=","Bloom","(","your_model_path",")",">",">",">","tokens","=","llm._tokenize","(","b","''","Learning","English","is","''",")",">",">",">","for","token","in","llm._generate","(","tokens",")",":",">",">",">","print","(","llm.detokenize","(","[","token","]",")",".decode","(","``","utf-8","''",",","errors=","''","ignore","''",")",")","Args",":","tokens",":","The","prompt","tokens",".","Yields",":","The","generated","tokens","."]
code: def _generate(
      self,
      tokens: Sequence[int],
      top_k: int = 40,
      top_p: float = 0.95,
      temp: float = 0.80,
      repeat_penalty: float = 1.1,
      reset: bool = True,
      frequency_penalty: float = 0.0,
      presence_penalty: float = 0.0,
      tfs_z: float = 1.0,
      mirostat_mode: int = 0,
      mirostat_tau: float = 5.0,
      mirostat_eta: float = 0.1,
  ) -> Generator[int, Optional[Sequence[int]], None]:
      """Create a generator of tokens from a prompt.
  
      Examples:
          >>> llm = Bloom(your_model_path)
          >>> tokens = llm._tokenize(b"Learning English is")
          >>> for token in llm._generate(tokens):
          >>>     print(llm.detokenize([token]).decode("utf-8", errors="ignore"))
  
      Args:
          tokens: The prompt tokens.
  
      Yields:
          The generated tokens.
      """
      # TODO: Some parameters are temporarily not supported
      # Unsupported parameters are checked in `_supported_generate`
      return self._supported_generate(
          tokens,
          top_k,
          top_p,
          temp,
          repeat_penalty,
          reset,
          frequency_penalty,
          presence_penalty,
          tfs_z,
          mirostat_mode,
          mirostat_tau,
          mirostat_eta,
      )
  
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 10 for calling the Bloom obj's underlying member method code with example usage: obj._generate(tokens, top_k, top_p, temp, repeat_penalty, reset, frequency_penalty, presence_penalty, tfs_z, mirostat_mode, mirostat_tau, mirostat_eta) and returns: self