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Fix documentation links always pointing to master. (#9217)

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* Use extlinks to point hyperlink with the version of code

* Point to version on release and master until then

* Apply style

* Correct links

* Add missing backtick

* Simple missing backtick after all.

Co-authored-by: Raghavendra Sugeeth P S <raghav-5305@raghav-5305.csez.zohocorpin.com>
Co-authored-by: Lysandre <lysandre.debut@reseau.eseo.fr>
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Sugeeth
2021-01-05 16:48:48 +05:30
committed by GitHub
parent 52d62e686c
commit 314cca2842
13 changed files with 45 additions and 57 deletions
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10
docs/source/converting_tensorflow_models.rst
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@@ -27,9 +27,8 @@ BERT
You can convert any TensorFlow checkpoint for BERT (in particular `the pre-trained models released by Google
<https://github.com/google-research/bert#pre-trained-models>`_\ ) in a PyTorch save file by using the
`convert_bert_original_tf_checkpoint_to_pytorch.py
<https://github.com/huggingface/transformers/blob/master/src/transformers/convert_bert_original_tf_checkpoint_to_pytorch.py>`_
script.
:prefix_link:`convert_bert_original_tf_checkpoint_to_pytorch.py
<src/transformers/convert_bert_original_tf_checkpoint_to_pytorch.py>` script.
This CLI takes as input a TensorFlow checkpoint (three files starting with ``bert_model.ckpt``\ ) and the associated
configuration file (\ ``bert_config.json``\ ), and creates a PyTorch model for this configuration, loads the weights
@@ -66,9 +65,8 @@ ALBERT
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
Convert TensorFlow model checkpoints of ALBERT to PyTorch using the
`convert_albert_original_tf_checkpoint_to_pytorch.py
<https://github.com/huggingface/transformers/blob/master/src/transformers/convert_bert_original_tf_checkpoint_to_pytorch.py>`_
script.
:prefix_link:`convert_albert_original_tf_checkpoint_to_pytorch.py
<src/transformers/convert_bert_original_tf_checkpoint_to_pytorch.py>` script.
The CLI takes as input a TensorFlow checkpoint (three files starting with ``model.ckpt-best``\ ) and the accompanying
configuration file (\ ``albert_config.json``\ ), then creates and saves a PyTorch model. To run this conversion you