Unverified Commit 6b83090e authored by Reza Gharibi's avatar Reza Gharibi Committed by GitHub
Browse files

Fix some typos in the docs (#14126)

* Fix some typos in the docs

* Fix a styling issue

* Fix code quality check error
parent 95bab538
...@@ -166,7 +166,7 @@ Values that should be put in `code` should either be surrounded by double backti ...@@ -166,7 +166,7 @@ Values that should be put in `code` should either be surrounded by double backti
an object using the :obj: syntax: :obj:\`like so\`. Note that argument names and objects like True, None or any strings an object using the :obj: syntax: :obj:\`like so\`. Note that argument names and objects like True, None or any strings
should usually be put in `code`. should usually be put in `code`.
When mentionning a class, it is recommended to use the :class: syntax as the mentioned class will be automatically When mentioning a class, it is recommended to use the :class: syntax as the mentioned class will be automatically
linked by Sphinx: :class:\`~transformers.XXXClass\` linked by Sphinx: :class:\`~transformers.XXXClass\`
When mentioning a function, it is recommended to use the :func: syntax as the mentioned function will be automatically When mentioning a function, it is recommended to use the :func: syntax as the mentioned function will be automatically
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...@@ -81,7 +81,7 @@ pip install git+https://github.com/huggingface/transformers ...@@ -81,7 +81,7 @@ pip install git+https://github.com/huggingface/transformers
Note that this will install not the latest released version, but the bleeding edge `master` version, which you may want to use in case a bug has been fixed since the last official release and a new release hasn't been yet rolled out. Note that this will install not the latest released version, but the bleeding edge `master` version, which you may want to use in case a bug has been fixed since the last official release and a new release hasn't been yet rolled out.
While we strive to keep `master` operational at all times, if you notice some issues, they usually get fixed within a few hours or a day and and you're more than welcome to help us detect any problems by opening an [Issue](https://github.com/huggingface/transformers/issues) and this way, things will get fixed even sooner. While we strive to keep `master` operational at all times, if you notice some issues, they usually get fixed within a few hours or a day and you're more than welcome to help us detect any problems by opening an [Issue](https://github.com/huggingface/transformers/issues) and this way, things will get fixed even sooner.
Again, you can run: Again, you can run:
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...@@ -76,7 +76,7 @@ Transformers: ...@@ -76,7 +76,7 @@ Transformers:
It will store your access token in the Hugging Face cache folder (by default :obj:`~/.cache/`). It will store your access token in the Hugging Face cache folder (by default :obj:`~/.cache/`).
If you don't have an easy access to a terminal (for instance in a Colab session), you can find a token linked to your If you don't have an easy access to a terminal (for instance in a Colab session), you can find a token linked to your
acount by going on `huggingface.co <https://huggingface.co/>`, click on your avatar on the top left corner, then on account by going on `huggingface.co <https://huggingface.co/>`, click on your avatar on the top left corner, then on
`Edit profile` on the left, just beneath your profile picture. In the submenu `API Tokens`, you will find your API `Edit profile` on the left, just beneath your profile picture. In the submenu `API Tokens`, you will find your API
token that you can just copy. token that you can just copy.
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...@@ -182,9 +182,10 @@ base vocabulary, we obtain: ...@@ -182,9 +182,10 @@ base vocabulary, we obtain:
BPE then counts the frequency of each possible symbol pair and picks the symbol pair that occurs most frequently. In BPE then counts the frequency of each possible symbol pair and picks the symbol pair that occurs most frequently. In
the example above ``"h"`` followed by ``"u"`` is present `10 + 5 = 15` times (10 times in the 10 occurrences of the example above ``"h"`` followed by ``"u"`` is present `10 + 5 = 15` times (10 times in the 10 occurrences of
``"hug"``, 5 times in the 5 occurrences of "hugs"). However, the most frequent symbol pair is ``"u"`` followed by "g", ``"hug"``, 5 times in the 5 occurrences of ``"hugs"``). However, the most frequent symbol pair is ``"u"`` followed by
occurring `10 + 5 + 5 = 20` times in total. Thus, the first merge rule the tokenizer learns is to group all ``"u"`` ``"g"``, occurring `10 + 5 + 5 = 20` times in total. Thus, the first merge rule the tokenizer learns is to group all
symbols followed by a ``"g"`` symbol together. Next, "ug" is added to the vocabulary. The set of words then becomes ``"u"`` symbols followed by a ``"g"`` symbol together. Next, ``"ug"`` is added to the vocabulary. The set of words then
becomes
.. code-block:: .. code-block::
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...@@ -335,7 +335,7 @@ scheduler. The default optimizer used by the :class:`~transformers.Trainer` is : ...@@ -335,7 +335,7 @@ scheduler. The default optimizer used by the :class:`~transformers.Trainer` is :
optimizer = AdamW(model.parameters(), lr=5e-5) optimizer = AdamW(model.parameters(), lr=5e-5)
Finally, the learning rate scheduler used by default it just a linear decay form the maximum value (5e-5 here) to 0: Finally, the learning rate scheduler used by default is just a linear decay from the maximum value (5e-5 here) to 0:
.. code-block:: python .. code-block:: python
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