class_docstr: .. versionadded:: 1.2.0
code: def _create_embeddings(self, texts):
      if self.use_differentiable_head:
          raise NotImplementedError()
      else:
          embeddings = self.model.model_body.encode(
              texts, device=self.device
          )
          proba = self.model.model_head.predict_proba(embeddings)
  
      return embeddings, proba
  
imports: import types
  import numpy
  from sklearn.exceptions import NotFittedError
  from sklearn.utils.validation import check_is_fitted
  from small_text.base import check_optional_dependency
  from small_text.classifiers.classification import Classifier, EmbeddingMixin
  from small_text.exceptions import UnsupportedOperationException
  from small_text.utils.classification import empty_result, _multi_label_list_to_multi_hot, prediction_result
  from small_text.utils.context import build_pbar_context
  from small_text.utils.labels import csr_to_list
  from small_text.integrations.transformers.classifiers.base import ModelLoadingStrategy
label_desc: Use image node_id 2 for calling the SetFitClassificationEmbeddingMixin obj's underlying member method code with example usage: obj._create_embeddings(texts) and returns: embeddings,  proba