class_docstr: Factory class to create instances of Sentence Transformers embedding backends.
code: def get_embedding_backend(
      model: str,
      device: Optional[str] = None,
      use_auth_token: Union[bool, str, None] = None,
  ):
      embedding_backend_id = f"{model}{device}{use_auth_token}"
  
      if (
          embedding_backend_id
          in _SentenceTransformersEmbeddingBackendFactory._instances
      ):
          return (
              _SentenceTransformersEmbeddingBackendFactory._instances[
                  embedding_backend_id
              ]
          )
      embedding_backend = _SentenceTransformersEmbeddingBackend(
          model=model, device=device, use_auth_token=use_auth_token
      )
      _SentenceTransformersEmbeddingBackendFactory._instances[
          embedding_backend_id
      ] = embedding_backend
      return embedding_backend
  
imports: from typing import List, Optional, Union, Dict
  from haystack.lazy_imports import LazyImport
label_desc: Use image node_id 1 for calling the _SentenceTransformersEmbeddingBackendFactory obj's underlying member method code with example usage: obj.get_embedding_backend(model, device, use_auth_token) and returns: embedding_backend, _SentenceTransformersEmbeddingBackendFactory