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Switch return_dict to True by default. (#8530)

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* Use the CI to identify failing tests

* Remove from all examples and tests

* More default switch

* Fixes

* More test fixes

* More fixes

* Last fixes hopefully

* Use the CI to identify failing tests

* Remove from all examples and tests

* More default switch

* Fixes

* More test fixes

* More fixes

* Last fixes hopefully

* Run on the real suite

* Fix slow tests
This commit is contained in:
Sylvain Gugger
2020-11-16 11:43:00 -05:00
committed by GitHub
parent 0d0a0785fd
commit 1073a2bde5
106 changed files with 138 additions and 234 deletions
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docs/source/training.rst
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@@ -39,7 +39,7 @@ head on top of the encoder with an output size of 2. Models are initialized in `
.. code-block:: python
from transformers import BertForSequenceClassification
model = BertForSequenceClassification.from_pretrained('bert-base-uncased', return_dict=True)
model = BertForSequenceClassification.from_pretrained('bert-base-uncased')
model.train()
This is useful because it allows us to make use of the pre-trained BERT encoder and easily train it on whatever