code: def __init__(
      self,
      model: torch.nn.Module,
      tokenizer: PreTrainedTokenizerBase,
      requires_padding: bool,
      dtype: torch.dtype,
      device: torch.device,
      rank: int = 0,
      world_size: int = 1,
      sliding_window: Optional[int] = None,
      speculate: Optional[int] = None,
  ):
      self.model = model.eval()
      self.tokenizer = tokenizer
      self.all_special_ids = set(tokenizer.all_special_ids)
      self.requires_padding = requires_padding
      self.dtype = dtype
      self.device = device
      self.rank = rank
      self.world_size = world_size
      self.sliding_window = (
          sliding_window if sliding_window != -1 else None
      )
  
      if speculate is None:
          speculate = get_speculate()
      self.speculate = speculate
  
      self.has_position_ids = (
          inspect.signature(model.forward).parameters.get(
              "position_ids", None
          )
          is not None
      )
  
      self.check_initialized()
  
file_path: text-generation-inference/server/text_generation_server/models/model.py
imports: import inspect
  import torch
  from abc import ABC, abstractmethod
  from typing import List, Tuple, Optional, TypeVar, Type
  from transformers import PreTrainedTokenizerBase, PretrainedConfig
  from text_generation_server.models.types import Batch, Generation
  from text_generation_server.utils.speculate import get_speculate
  from text_generation_server.pb.generate_pb2 import InfoResponse
label_desc: Use image node_id 1 to create a new Model object from inherited base classes: ABC with example: obj = Model(model, tokenizer, requires_padding, dtype, device, rank, world_size, sliding_window, speculate)