MrBERT-es

>>> from transformers import pipeline
>>> from pprint import pprint

>>> unmasker = pipeline('fill-mask', model='BSC-LT/MrBERT-es')

>>> pprint(unmasker("Me encanta la<mask>de Barcelona.",top_k=3))
[{'score': 0.2312059849500656,
  'sequence': 'Me encanta la ciudad de Barcelona.',
  'token': 2634,
  'token_str': 'ciudad'},
 {'score': 0.0812854915857315,
  'sequence': 'Me encanta la gente de Barcelona.',
  'token': 4475,
  'token_str': 'gente'},
 {'score': 0.07678654044866562,
  'sequence': 'Me encanta la gastronomía de Barcelona.',
  'token': 18096,
  'token_str': 'gastronomía'}]
>>> pprint(unmasker("La ciencia engloba disciplinas como la<mask>y las matemáticas.",top_k=3))
[{'score': 0.8801143765449524,
  'sequence': 'La ciencia engloba disciplinas como la física y las '
              'matemáticas.',
  'token': 9204,
  'token_str': 'física'},
 {'score': 0.07342680543661118,
  'sequence': 'La ciencia engloba disciplinas como la biología y las '
              'matemáticas.',
  'token': 40678,
  'token_str': 'biología'},
 {'score': 0.02307266741991043,
  'sequence': 'La ciencia engloba disciplinas como la química y las '
              'matemáticas.',
  'token': 25047,
  'token_str': 'química'}]
>>> pprint(unmasker("Since I can't conquer the world yet, I'll just hide my weights under your<mask>and wait patiently.", top_k=3))
[{'score': 0.12437283992767334,
  'sequence': "Since I can't conquer the world yet, I'll just hide my weights "
              'under your pillow and wait patiently.',
  'token': 40389,
  'token_str': 'pillow'},
 {'score': 0.09473687410354614,
  'sequence': "Since I can't conquer the world yet, I'll just hide my weights "
              'under your arm and wait patiently.',
  'token': 6198,
  'token_str': 'arm'},
 {'score': 0.08770021051168442,
  'sequence': "Since I can't conquer the world yet, I'll just hide my weights "
              'under your feet and wait patiently.',
  'token': 6985,
  'token_str': 'feet'}]