class_docstr: Inference model implementation for ragged batching for Llama-2 models.
class_docstr_tok: ["Inference","model","implementation","for","ragged","batching","for","Llama-2","models","."]
docstr: The positional embedding configuration for the model.
docstr_tok: ["The","positional","embedding","configuration","for","the","model","."]
code: def positional_embedding_config(self) -> RotateHalfConfig:
      """
      The positional embedding configuration for the model.
      """
      return RotateHalfConfig()
  
imports: from typing import Iterable, Optional, Tuple
  import torch
  import deepspeed.comm
  from ...allocator import empty_from
  from ...inference_utils import ActivationType, DtypeEnum
  from ..None import *
  from ...modules.configs import *
  from ...modules.interfaces import *
  from ...ragged import RaggedBatchWrapper
  from .container import FalconNonTransformerContainer, FalconTransformerContainer
label_desc: Use image node_id 13 for calling the FalconInferenceModel obj's underlying member method code with example usage: obj.positional_embedding_config() and returns: RotateHalfConfig