DistilBERT

from transformers import TFDistilBertForMaskedLM, AutoTokenizer

model = TFDistilBertForMaskedLM.from_pretrained('distilbert-base-uncased')

tokenizer = AutoTokenizer.from_pretrained('distilbert-base-uncased')

inputs = tokenizer('Apple is my [MASK] food.', return_tensors='tf')

result = model(inputs)

logits = result[0]

import tensorflow as tf
top = tf.math.top_k(logits[0, 4], k=5)

tokenizer.decode(top.indices.numpy())

'favorite favourite staple preferred everyday'

from transformers import pipeline

pip = pipeline('fill-mask', model='distilbert-base-uncased')

pip('Apple is my [MASK] food.')

[{'score': 0.8198481202125549,
  'sequence': '[CLS] apple is my favorite food. [SEP]',
  'token': 5440,
  'token_str': 'favorite'},
 {'score': 0.1563291996717453,
  'sequence': '[CLS] apple is my favourite food. [SEP]',
  'token': 8837,
  'token_str': 'favourite'},
 {'score': 0.011957455426454544,
  'sequence': '[CLS] apple is my staple food. [SEP]',
  'token': 18785,
  'token_str': 'staple'},
 {'score': 0.0021453669760376215,
  'sequence': '[CLS] apple is my preferred food. [SEP]',
  'token': 6871,
  'token_str': 'preferred'},
 {'score': 0.0007646055892109871,
  'sequence': '[CLS] apple is my everyday food. [SEP]',
  'token': 10126,
  'token_str': 'everyday'}]

from transformers import FillMaskPipeline
pip2 = FillMaskPipeline(model=model, tokenizer=tokenizer)

pip2('Apple is my [MASK] food.')

[{'score': 0.8198353052139282,
  'sequence': '[CLS] apple is my favorite food. [SEP]',
  'token': 5440,
  'token_str': 'favorite'},
 {'score': 0.15632735192775726,
  'sequence': '[CLS] apple is my favourite food. [SEP]',
  'token': 8837,
  'token_str': 'favourite'},
 {'score': 0.011957302689552307,
  'sequence': '[CLS] apple is my staple food. [SEP]',
  'token': 18785,
  'token_str': 'staple'},
 {'score': 0.0021453213412314653,
  'sequence': '[CLS] apple is my preferred food. [SEP]',
  'token': 6871,
  'token_str': 'preferred'},
 {'score': 0.000764592201448977,
  'sequence': '[CLS] apple is my everyday food. [SEP]',
  'token': 10126,
  'token_str': 'everyday'}]