def test_tc_save():
happy = HappyTextClassification()
happy.save("model/")
result_before = happy.classify_text("What a great movie")
happy = HappyTextClassification(load_path="model/")
result_after = happy.classify_text("What a great movie")
assert result_before.label == result_after.label
def test_classify_text():
happy_tc = HappyTextClassification(
model_type="DISTILBERT",
model_name="distilbert-base-uncased-finetuned-sst-2-english")
result = happy_tc.classify_text("What a great movie")
assert result.label == 'POSITIVE'
assert result.score > 0.9
def example_2_1():
happy_tc = HappyTextClassification(
model_type="DISTILBERT",
model_name="distilbert-base-uncased-finetuned-sst-2-english")
result = happy_tc.classify_text("Great movie! 5/5")
print(
type(result)
) # <class 'happytransformer.happy_text_classification.TextClassificationResult'>
print(
result
) # TextClassificationResult(label='LABEL_1', score=0.9998761415481567)
print(result.label) # LABEL_1