code: def distilbert_base_uncased_model() -> SentenceTransformer:
      word_embedding_model = Transformer("distilbert-base-uncased")
      pooling_model = Pooling(
          word_embedding_model.get_word_embedding_dimension()
      )
      model = SentenceTransformer(
          modules=[word_embedding_model, pooling_model]
      )
      return model
  
file_path: sentence-transformers/tests/conftest.py
imports: import pytest
  from sentence_transformers import SentenceTransformer, CrossEncoder
  from sentence_transformers.models import Transformer, Pooling
label_desc: Use image node_id 5 for calling a global function with example usage: distilbert_base_uncased_model() and returns: model