class_docstr: Class to manage Sentence Transformers embeddings.
code: def embed(self, data: List[str], **kwargs) -> List[List[float]]:
      embeddings = self.model.encode(data, **kwargs).tolist()
      return embeddings
  
imports: from typing import List, Optional, Union, Dict
  from haystack.lazy_imports import LazyImport
label_desc: Use image node_id 2 for calling the _SentenceTransformersEmbeddingBackend obj's underlying member method code with example usage: obj.embed(data) and returns: embeddings