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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>
This commit is contained in:
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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2
docs/source/model_doc/bart.rst
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@@ -42,7 +42,7 @@ Examples
_______________________________________________________________________________________________________________________
- Examples and scripts for fine-tuning BART and other models for sequence to sequence tasks can be found in
`examples/seq2seq/ <https://github.com/huggingface/transformers/blob/master/examples/seq2seq/README.md>`__.
:prefix_link:`examples/seq2seq/ <examples/seq2seq/README.md>`.
- An example of how to train :class:`~transformers.BartForConditionalGeneration` with a Hugging Face :obj:`datasets`
object can be found in this `forum discussion
<https://discuss.huggingface.co/t/train-bart-for-conditional-generation-e-g-summarization/1904>`__.

4
docs/source/model_doc/barthez.rst
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@@ -41,8 +41,8 @@ The Authors' code can be found `here <https://github.com/moussaKam/BARThez>`__.
Examples
_______________________________________________________________________________________________________________________
- BARThez can be fine-tuned on sequence-to-sequence tasks in a similar way as BART, check: `examples/seq2seq/
<https://github.com/huggingface/transformers/blob/master/examples/seq2seq/README.md>`__.
- BARThez can be fine-tuned on sequence-to-sequence tasks in a similar way as BART, check:
:prefix_link:`examples/seq2seq/ <examples/seq2seq/README.md>`.
BarthezTokenizer

9
docs/source/model_doc/marian.rst
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@@ -56,12 +56,9 @@ Examples
- Since Marian models are smaller than many other translation models available in the library, they can be useful for
fine-tuning experiments and integration tests.
- `Fine-tune on TPU
<https://github.com/huggingface/transformers/blob/master/examples/seq2seq/builtin_trainer/train_distil_marian_enro_tpu.sh>`__
- `Fine-tune on GPU
<https://github.com/huggingface/transformers/blob/master/examples/seq2seq/builtin_trainer/train_distil_marian_enro.sh>`__
- `Fine-tune on GPU with pytorch-lightning
<https://github.com/huggingface/transformers/blob/master/examples/seq2seq/distil_marian_no_teacher.sh>`__
- :prefix_link:`Fine-tune on TPU <examples/seq2seq/builtin_trainer/train_distil_marian_enro_tpu.sh>`
- :prefix_link:`Fine-tune on GPU <examples/seq2seq/builtin_trainer/train_distil_marian_enro.sh>`
- :prefix_link:`Fine-tune on GPU with pytorch-lightning <examples/seq2seq/distil_marian_no_teacher.sh>`
Multilingual Models
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

2
docs/source/model_doc/mbart.rst
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@@ -35,7 +35,7 @@ Examples
_______________________________________________________________________________________________________________________
- Examples and scripts for fine-tuning mBART and other models for sequence to sequence tasks can be found in
`examples/seq2seq/ <https://github.com/huggingface/transformers/blob/master/examples/seq2seq/README.md>`__.
:prefix_link:`examples/seq2seq/ <examples/seq2seq/README.md>`.
- Given the large embeddings table, mBART consumes a large amount of GPU RAM, especially for fine-tuning.
:class:`MarianMTModel` is usually a better choice for bilingual machine translation.

5
docs/source/model_doc/pegasus.rst
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@@ -51,9 +51,8 @@ All the `checkpoints <https://huggingface.co/models?search=pegasus>`__ are fine-
Examples
_______________________________________________________________________________________________________________________
- `Script <https://github.com/huggingface/transformers/blob/master/examples/seq2seq/finetune_pegasus_xsum.sh>`__ to
fine-tune pegasus on the XSUM dataset. Data download instructions at `examples/seq2seq/
<https://github.com/huggingface/transformers/blob/master/examples/seq2seq/README.md>`__.
- :prefix_link:`Script <examples/seq2seq/finetune_pegasus_xsum.sh>` to fine-tune pegasus on the XSUM dataset. Data
download instructions at :prefix_link:`examples/seq2seq/ <examples/seq2seq/README.md>`.
- FP16 is not supported (help/ideas on this appreciated!).
- The adafactor optimizer is recommended for pegasus fine-tuning.