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@@ -75,7 +75,8 @@ You can use the raw model for fill mask or fine-tune it to a downstream task.
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  ## How to use
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  Here is how to use this model:
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- ```python
 
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  >>> from transformers import pipeline
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  >>> from pprint import pprint
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  >>> unmasker = pipeline('fill-mask', model='PlanTL-GOB-ES/roberta-base-bne')
@@ -100,7 +101,6 @@ Here is how to use this model:
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  'token': 31915,
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  'token_str': ' validar',
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  'sequence': 'Gracias a los datos de la BNE se ha podido validar este modelo del lenguaje.'}]
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-
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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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  ## How to use
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  Here is how to use this model:
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+ ```
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+ python
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  >>> from transformers import pipeline
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  >>> from pprint import pprint
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  >>> unmasker = pipeline('fill-mask', model='PlanTL-GOB-ES/roberta-base-bne')
 
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  'token': 31915,
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  'token_str': ' validar',
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  'sequence': 'Gracias a los datos de la BNE se ha podido validar este modelo del lenguaje.'}]
 
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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: