Tips + whitespaces

This commit is contained in:
Lysandre
2020-01-21 15:58:25 -05:00
committed by Lysandre Debut
parent 0e9899f451
commit 9ddf60b694
34 changed files with 452 additions and 369 deletions

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@@ -1,8 +1,11 @@
Transformer XL
----------------------------------------------------
Overview
~~~~~~~~~~~~~~~~~~~~~
The Transformer-XL model was proposed in
`Transformer-XL: Attentive Language Models Beyond a Fixed-Length Context`_
`Transformer-XL: Attentive Language Models Beyond a Fixed-Length Context <https://arxiv.org/abs/1901.02860>`__
by Zihang Dai*, Zhilin Yang*, Yiming Yang, Jaime Carbonell, Quoc V. Le, Ruslan Salakhutdinov.
It's a causal (uni-directional) transformer with relative positioning (sinusoïdal) embeddings which can reuse
previously computed hidden-states to attend to longer context (memory).
@@ -23,46 +26,47 @@ coherent, novel text articles with thousands of tokens.*
Tips:
- Transformer-XL uses relative sinusoidal positional embeddings so it's usually advised to pad the inputs on
the left rather than the right.
- Transformer-XL uses relative sinusoidal positional embeddings. Padding can be done on the left or on the right.
The original implementation trains on SQuAD with padding on the left, therefore the padding defaults are set to left.
- Transformer-XL is one of the few models that has no sequence length limit.
``TransfoXLConfig``
TransfoXLConfig
~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: transformers.TransfoXLConfig
:members:
``TransfoXLTokenizer``
TransfoXLTokenizer
~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: transformers.TransfoXLTokenizer
:members:
``TransfoXLModel``
TransfoXLModel
~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: transformers.TransfoXLModel
:members:
``TransfoXLLMHeadModel``
TransfoXLLMHeadModel
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: transformers.TransfoXLLMHeadModel
:members:
``TFTransfoXLModel``
TFTransfoXLModel
~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: transformers.TFTransfoXLModel
:members:
``TFTransfoXLLMHeadModel``
TFTransfoXLLMHeadModel
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: transformers.TFTransfoXLLMHeadModel