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 __init__(
      self, path_or_splitname: str, max_examples: Optional[int] = None
  ):
      if path_or_splitname.endswith(".csv"):
          self._examples = self.load_from_csv(path_or_splitname)[
              :max_examples
          ]
      else:
          self._examples = self.load_from_tfds(path_or_splitname)[
              :max_examples
          ]
  
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 3 to create a new STSBData object from inherited base classes: lit_dataset with example: obj = STSBData(path_or_splitname, max_examples)