May 31, 2024 · Neural networks for machine translation typically contain an encoder reading the input sentence and generating a representation of it. A decoder then generates the output sentence word by word while consulting the representation generated by the encoder.

Feb 27, 2025 · The transformer model is built on an encoder-decoder architecture where both the encoder and decoder are composed of a series of layers that utilize self-attention mechanisms and feed-forward neural networks.

Aug 16, 2024 · The Encoder-Decoder architecture is a fundamental concept in machine learning, especially in tasks involving sequences such as machine translation, text summarization, and image captioning.

Oct 31, 2019 · The encoder-decoder model is a way of using recurrent neural networks for sequence-to-sequence prediction problems. It was initially developed for machine translation...

Dec 12, 2021 · The transformer uses an encoder-decoder architecture. The encoder extracts features from an input sentence, and the decoder uses the features to produce an output sentence (translation). The encoder in the transformer consists of multiple encoder blocks.

Jan 16, 2024 · The Transformer architecture was initially introduced by Vaswani et al. in 2017 for sequence-to-sequence tasks, particularly machine translation. The original transformer architecture was based on the encoder-decoder architecture for performing tasks such as machine translation.

The goal of the blog post is to give an in-detail explanation of how the transformer-based encoder-decoder architecture models sequence-to-sequence problems. We will focus on the mathematical model defined by the architecture and how the model can be used in inference.

Mar 29, 2025 · The Transformer Architecture. The original transformer architecture is composed of an encoder and a decoder. Its layout is shown in the figure below. Recall that the transformer model was developed for translation tasks, replacing the seq2seq architecture that was commonly used with RNNs. Therefore, it borrowed the encoder-decoder architecture.

Feb 17, 2025 · Transformer models have shown promise in a number of machine learning tasks and their use in translation has produced state-of-the-art models and performance. This article will walk you...

Mar 26, 2025 · 7. Transformer Model. This block defines the main Transformer class which combines the encoder and decoder layers. It also includes the embedding layers and the final output layer. self.encoder_embedding = nn.Embedding(src_vocab_size, d_model): Initializes the embedding layer for the source sequence, mapping tokens to continuous vectors of size ...