class_docstr: Load sentences from a flat text file.
class_docstr_tok: ["Load","sentences","from","a","flat","text","file","."]
code: def __init__(
      self,
      path_or_glob: str,
      skiplines: int = 0,
      max_examples: Optional[int] = None,
  ):
      self._examples = self.load_datapoints(
          path_or_glob, skiplines=skiplines
      )[:max_examples]
  
file_path: lit/lit_nlp/examples/datasets/lm.py
imports: import glob
  from typing import Optional
  from lit_nlp.api import dataset
  from lit_nlp.api import types
  import tensorflow_datasets
label_desc: Use image node_id 1 to create a new PlaintextSents object from inherited base classes: lit_dataset with example: obj = PlaintextSents(path_or_glob, skiplines, max_examples)