class_docstr: Handler class for Instruction Embedding models.
  Refer to the README for how to use Instructor models and this handler.
code: def handle(self, data, context):
      inputs = data[0].get("body").get("inputs")
      if isinstance(inputs[0], str):
          # single inference
          inputs = [inputs]
      pred_embeddings = self.model.encode(inputs)
      return [pred_embeddings.tolist()]
  
file_path: serve/examples/instruction_embedding/instructor_embedding_handler.py
imports: import logging
  from InstructorEmbedding import INSTRUCTOR
  from ts.torch_handler.base_handler import BaseHandler
label_desc: Use image node_id 3 for calling the InstructorEmbeddingHandler obj's underlying member method code with example usage: obj.handle(data, context) and returns: list