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Update README.md
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README.md
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@@ -32,9 +32,28 @@ You can use this model directly with a pipeline for masked language modeling:
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```python
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>>> from transformers import pipeline
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>>> unmasker = pipeline('fill-mask', model='facebook/xlm-roberta-xl')
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>>> unmasker("
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```
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Here is how to use this model to get the features of a given text in PyTorch:
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```python
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>>> from transformers import pipeline
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>>> unmasker = pipeline('fill-mask', model='facebook/xlm-roberta-xl')
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>>> unmasker("Europe is a <mask> continent.")
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[{'score': 0.08562745153903961,
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'token': 38043,
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'token_str': 'living',
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'sequence': 'Europe is a living continent.'},
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{'score': 0.0799778401851654,
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'token': 103494,
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'token_str': 'dead',
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'sequence': 'Europe is a dead continent.'},
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{'score': 0.046154674142599106,
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'token': 72856,
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'token_str': 'lost',
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'sequence': 'Europe is a lost continent.'},
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{'score': 0.04358183592557907,
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'token': 19336,
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'token_str': 'small',
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'sequence': 'Europe is a small continent.'},
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{'score': 0.040570393204689026,
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'token': 34923,
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'token_str': 'beautiful',
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'sequence': 'Europe is a beautiful continent.'}]
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```
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Here is how to use this model to get the features of a given text in PyTorch:
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