code: def test_token_labeling():
      sentence = Sentence("This sentence will be labled")
      assert sentence.get_labels("ner") == []
      assert sentence.get_labels() == []
      sentence[2].add_label("ner", "B-promise")
      sentence[3].add_label("ner", "I-promise")
      sentence[4].add_label("ner", "I-promise")
      assert [label.value for label in sentence.get_labels()] == [
          "B-promise",
          "I-promise",
          "I-promise",
      ]
      assert [token.get_label("ner").value for token in sentence] == [
          "O",
          "O",
          "B-promise",
          "I-promise",
          "I-promise",
      ]
      sentence[1].set_label("ner", "B-object")
      sentence[1].set_label("ner", "B-subject")
      assert [label.value for label in sentence.get_labels("ner")] == [
          "B-subject",
          "B-promise",
          "I-promise",
          "I-promise",
      ]
      assert [token.get_label("ner").value for token in sentence] == [
          "O",
          "B-subject",
          "B-promise",
          "I-promise",
          "I-promise",
      ]
      sentence.set_label("class", "positive")
      sentence.remove_labels("ner")
      assert sentence.get_labels("ner") == []
      assert [label.value for label in sentence.get_labels()] == [
          "positive"
      ]
      sentence[0].add_label("pos", "first")
      sentence[0].add_label("pos", "primero")
      sentence[0].add_label("pos", "erstes")
      assert [label.value for label in sentence.get_labels("pos")] == [
          "first",
          "primero",
          "erstes",
      ]
      assert sentence[0].get_label("pos").value == "first"
  
imports: from flair.data import Sentence
label_desc: Use image node_id 3 for calling a global function with example usage: test_token_labeling() without return types