Vektoromformere
Vektoromformere, also known as vector transformers, are a type of machine learning model designed to process and generate sequences of data. They are an extension of the transformer architecture, which was originally introduced for natural language processing tasks. The key innovation of vektoromformere is their ability to handle vector-based inputs and outputs, making them versatile for a wide range of applications beyond text, such as time series forecasting, audio processing, and even image generation.
The architecture of vektoromformere consists of an encoder and a decoder, both of which are composed of
One of the main advantages of vektoromformere is their ability to handle variable-length sequences, making them
Vektoromformere have been successfully applied to various domains, including machine translation, text summarization, and speech recognition.