Models doc (#7345)

* Clean up model documentation

* Formatting

* Preparation work

* Long lines

* Main work on rst files

* Cleanup all config files

* Syntax fix

* Clean all tokenizers

* Work on first models

* Models beginning

* FaluBERT

* All PyTorch models

* All models

* Long lines again

* Fixes

* More fixes

* Update docs/source/model_doc/bert.rst

Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

* Update docs/source/model_doc/electra.rst

Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

* Last fixes

Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
This commit is contained in:
Sylvain Gugger
2020-09-23 13:20:45 -04:00
committed by GitHub
parent 58405a527b
commit 3323146e90
165 changed files with 6907 additions and 5803 deletions

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@@ -1,12 +1,12 @@
CTRL
----------------------------------------------------
-----------------------------------------------------------------------------------------------------------------------
Overview
~~~~~~~~~~~~~~~~~~~~~
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
CTRL model was proposed in `CTRL: A Conditional Transformer Language Model for Controllable Generation <https://arxiv.org/abs/1909.05858>`_
by Nitish Shirish Keskar*, Bryan McCann*, Lav R. Varshney, Caiming Xiong and Richard Socher.
It's a causal (unidirectional) transformer pre-trained using language modeling on a very large
CTRL model was proposed in `CTRL: A Conditional Transformer Language Model for Controllable Generation
<https://arxiv.org/abs/1909.05858>`_ by Nitish Shirish Keskar*, Bryan McCann*, Lav R. Varshney, Caiming Xiong and
Richard Socher. It's a causal (unidirectional) transformer pre-trained using language modeling on a very large
corpus of ~140 GB of text data with the first token reserved as a control code (such as Links, Books, Wikipedia etc.).
The abstract from the paper is the following:
@@ -31,50 +31,50 @@ Tips:
it can be observed in the `run_generation.py` example script.
- The PyTorch models can take the `past` as input, which is the previously computed key/value attention pairs. Using
this `past` value prevents the model from re-computing pre-computed values in the context of text generation.
See `reusing the past in generative models <../quickstart.html#using-the-past>`_ for more information on the usage
See `reusing the past in generative models <../quickstart.html#using-the-past>`__ for more information on the usage
of this argument.
The original code can be found `here <https://github.com/salesforce/ctrl>`_.
The original code can be found `here <https://github.com/salesforce/ctrl>`__.
CTRLConfig
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.CTRLConfig
:members:
CTRLTokenizer
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.. autoclass:: transformers.CTRLTokenizer
:members: save_vocabulary
CTRLModel
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: transformers.CTRLModel
:members:
:members: forward
CTRLLMHeadModel
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: transformers.CTRLLMHeadModel
:members:
:members: forward
TFCTRLModel
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: transformers.TFCTRLModel
:members:
:members: call
TFCTRLLMHeadModel
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.. autoclass:: transformers.TFCTRLLMHeadModel
:members:
:members: call