100_classification.py [download]

#!/usr/bin/env python3

import datasets
import transformers
import random

classifier = transformers.pipeline("sentiment-analysis")

imdb = datasets.load_dataset("imdb")

print(list(imdb.keys()))
print(type(imdb["train"]))
print(imdb["train"][0])

for i in range(5):
    j = random.randrange(len(imdb["train"]))
    text = imdb["train"][j]["text"]
    label = imdb["train"][j]["label"]
    score = classifier(text)[0]['score']
    print("label: {}  score: {:.2f}  {}".format(label, score, text[:40]))

Last Updated 04/18/2024