The authors compared the model's performance on word-level and character-level datasets andcompared them to other prominent models(RNNs and Transformers).
We show that the Transformer generalizes well to other tasks by applying it successfully to English constituency parsing both with large and limited training data.
We propose a new simple network architecture, the Transformer, based solely on attention mechanisms, dispensing with recurrence and convolutions entirely.
The Transformer provides methods to set stylesheet parameters and serialization options(for example, whether output should be indented), and a method to actually run the transformation.
In addition, Tanzania's state-run power company Tanesco reportedlysigned a deal with China's TBEA Hengyang Transformer Co for“a rural electrification project”.
中文
Bahasa indonesia
日本語
عربى
Български
বাংলা
Český
Dansk
Deutsch
Ελληνικά
Español
Suomi
Français
עִברִית
हिंदी
Hrvatski
Magyar
Italiano
Қазақ
한국어
മലയാളം
मराठी
Bahasa malay
Nederlands
Norsk
Polski
Português
Română
Русский
Slovenský
Slovenski
Српски
Svenska
தமிழ்
తెలుగు
ไทย
Tagalog
Turkce
Українська
اردو
Tiếng việt