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@@ -144,23 +144,19 @@ We directly adapted this mechanism from Graves ([2016](#graves-2016)). At each i
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  The architecture is not yet directly included in the Transformers library. The code used for pre-training is available in the following [github repository](https://github.com/AntoineSimoulin/adaptive-depth-transformers). So you should install the code implementation first:
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  ```bash
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- pip install git+https://github.com/AntoineSimoulin/adaptive-depth-transformers
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  ```
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  Then you can use the model directly.
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  ```python
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- import sys
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- sys.path.append('adaptative-depth-transformers')
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-
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- from modeling_albert_act_tf import TFAlbertActModel
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- from modeling_albert_act import AlbertActModel
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- from configuration_albert_act import AlbertActConfig
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  from transformers import AlbertTokenizer
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- model = AlbertActModel.from_pretrained('asi/albert-act-base/')
 
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  _ = model.eval()
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- tokenizer = AlbertTokenizer.from_pretrained('asi/albert-act-base/')
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  inputs = tokenizer("a lump in the middle of the monkeys stirred and then fell quiet .", return_tensors="pt")
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  outputs = model(**inputs)
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  outputs.updates
 
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  The architecture is not yet directly included in the Transformers library. The code used for pre-training is available in the following [github repository](https://github.com/AntoineSimoulin/adaptive-depth-transformers). So you should install the code implementation first:
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  ```bash
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+ !pip install git+https://github.com/AntoineSimoulin/adaptive-depth-transformers$
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  ```
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  Then you can use the model directly.
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  ```python
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+ from act import AlbertActConfig, AlbertActModel, TFAlbertActModel
 
 
 
 
 
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  from transformers import AlbertTokenizer
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+ tokenizer = AlbertTokenizer.from_pretrained('asi/albert-act-base')
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+ model = AlbertActModel.from_pretrained('asi/albert-act-base')
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  _ = model.eval()
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+
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  inputs = tokenizer("a lump in the middle of the monkeys stirred and then fell quiet .", return_tensors="pt")
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  outputs = model(**inputs)
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  outputs.updates