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Update example

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@@ -59,7 +59,39 @@ 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='qwant/fralbert-base')
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- >>> unmasker("Bonjour Je suis un model [MASK] .")
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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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='qwant/fralbert-base')
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+ >>> unmasker("Paris est la capitale de la [MASK] .")
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+ [
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+ {
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+ "sequence": "paris est la capitale de la france.",
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+ "score": 0.6231236457824707,
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+ "token": 3043,
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+ "token_str": "france"
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+ },
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+ {
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+ "sequence": "paris est la capitale de la region.",
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+ "score": 0.2993471622467041,
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+ "token": 10531,
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+ "token_str": "region"
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+ },
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+ {
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+ "sequence": "paris est la capitale de la societe.",
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+ "score": 0.02028230018913746,
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+ "token": 24622,
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+ "token_str": "societe"
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+ },
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+ {
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+ "sequence": "paris est la capitale de la bretagne.",
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+ "score": 0.012089950032532215,
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+ "token": 24987,
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+ "token_str": "bretagne"
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+ },
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+ {
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+ "sequence": "paris est la capitale de la chine.",
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+ "score": 0.010002839379012585,
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+ "token": 14860,
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+ "token_str": "chine"
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+ }
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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: