   each token.
Zip together each token with its prediction and print it.
```py
from transformers import AutoModelForTokenClassification, AutoTokenizer
import torch
model = AutoModelForTokenClassification.from_pretrained("dbmdz/bert-large-cased-finetuned-conll03-english")
tokenizer = AutoTokenizer.from_pretrained("bert-base-cased")
sequence = (
...     "Hugging Face Inc. is a company based in New York City. Its headquarters are in DUMBO, "
...     "therefore very close to the Manhattan Bridge."
... )
inputs = tokenizer(sequence, return_tensors="pt")
tokens = inputs.tokens()
outputs = model(**inputs).logits
predictions = torch.argmax(outputs, dim=2)
===PT-TF-SPLIT===
from transformers import TFAutoModelForTokenClassification, AutoTokenizer
import tensorflow as tf
model = TFAutoModelForTokenClassification.from_pretrained("dbmdz/bert-large-cased-finetuned-conll03-english")
