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@@ -27,16 +27,8 @@ ColD Fusion-based model outperforms RoBERTa by 2.45 points in average without an
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  ### How to use
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-
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- You can use this model directly with a pipeline for masked language modeling:
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-
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- ```python
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- >>> from transformers import pipeline
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- >>> unmasker = pipeline('fill-mask', model='ibm/ColD-Fusion')
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- >>> unmasker("Hello I'm a <mask> model.")
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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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  ```python
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  from transformers import RobertaTokenizer, RobertaModel
 
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  ### How to use
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+ Best way to use is to finetune on your own task, but you can also extract features directly.
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+ To get the features of a given text in PyTorch:
 
 
 
 
 
 
 
 
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  ```python
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  from transformers import RobertaTokenizer, RobertaModel