is paraphrase: 90%
Should not be paraphrase
for i in range(len(classes)):
...     print(f"{classes[i]}: {int(round(not_paraphrase_results[i] * 100))}%")
not paraphrase: 94%
is paraphrase: 6%
===PT-TF-SPLIT===
from transformers import AutoTokenizer, TFAutoModelForSequenceClassification
import tensorflow as tf
tokenizer = AutoTokenizer.from_pretrained("bert-base-cased-finetuned-mrpc")
model = TFAutoModelForSequenceClassification.from_pretrained("bert-base-cased-finetuned-mrpc")
classes = ["not paraphrase", "is paraphrase"]
sequence_0 = "The company HuggingFace is based in New York City"
sequence_1 = "Apples are especially bad for your health"
sequence_2 = "HuggingFace's headquarters are situated in Manhattan"
The tokenizer will automatically add any model specific separators (i.e.  and ) and tokens to
