class_docstr: Semantic Textual Similarity Benchmark (STS-B).
  
  Unlike the other GLUE tasks, this is formulated as a regression problem.
  
  See https://www.tensorflow.org/datasets/catalog/glue#gluestsb.
class_docstr_tok: ["Semantic","Textual","Similarity","Benchmark","(","STS-B",")",".","Unlike","the","other","GLUE","tasks",",","this","is","formulated","as","a","regression","problem",".","See","https",":","\/\/www.tensorflow.org\/datasets\/catalog\/glue","#","gluestsb","."]
code: def load_from_tfds(self, split: str):
      if split not in self.TFDS_SPLITS:
          raise ValueError(
              f"Unsupported split '{split}'. Allowed values: {self.TFDS_SPLITS}"
          )
      ret = []
      for ex in load_tfds("glue/stsb", split=split):
          ret.append(
              {
                  "sentence1": ex["sentence1"].decode("utf-8"),
                  "sentence2": ex["sentence2"].decode("utf-8"),
                  "label": ex["label"],
              }
          )
      return ret
  
imports: from typing import Optional
  from lit_nlp.api import dataset
  from lit_nlp.api import types
  from lit_nlp.lib import file_cache
  from lit_nlp.lib import utils
  import pandas
  import tensorflow_datasets
label_desc: Use image node_id 2 for calling the STSBData obj's underlying member method code with example usage: obj.load_from_tfds(split) and returns: ret