But not all transformer applications require both the encoder and decoder module. For example, the GPT family of large language models uses stacks of decoder modules to generate text.

Figure 1: (a) In the architecture Encoder-Decoder, the input sequence is first encoded into a state vector, which is then used to decode the output sequence (b) A transformer layer, encoder and ...

In order to invert the resizing used to train the idea model, an encoder/decoder transformer can be trained. ... Concretely, in the diagram above, the expanded melspectrogram is 2048 columns long ...

global_information_extractor: This model is trained using a transformer encoder and decoder architecture, based on the configuration specified in Donut, to extract the overall summary of block diagram ...

Each swin transformer decoder block has two inputs: a feature from the encoder at the same layer, and a query vector. For the encoder’s features, 3-dimensional convolution is used to exploit the local ...