class_docstr: Load sentences from a flat text file.
class_docstr_tok: ["Load","sentences","from","a","flat","text","file","."]
code: def load_datapoints(self, path_or_glob: str, skiplines: int = 0):
      examples = []
      for path in glob.glob(path_or_glob):
          with open(path) as fd:
              for i, line in enumerate(fd):
                  if i < skiplines:  # skip header lines, if necessary
                      continue
                  line = line.strip()
                  if (
                      line
                  ):  # skip blank lines, these are usually document breaks
                      examples.append({"text": line})
      return 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 3 for calling the PlaintextSents obj's underlying member method code with example usage: obj.load_datapoints(path_or_glob, skiplines) and returns: examples