An encoder-decoder architecture is a powerful tool used in machine learning, specifically for tasks involving sequences like text or speech. It’s like a two-part machine that translates one form ...

Microsoft recently announced Mu, a new small language model designed to integrate with the Windows 11 UI experience. Mu will ...

Deepfakes are simple to make. A simple overview of the artificial intelligence (AI) behind deepfakes: Generative Adversarial Networks (GANs), Encoder-decoder pairs and First-Order Motion Models.

The encoder and decoder are lightweight models. The encoder takes in raw input bytes and creates the patch representations that are fed to the global transformer.

The HF library makes implementing NLP systems using TA models much less difficult (see "How to Create a Transformer Architecture Model for Natural Language Processing"). A good way to see where this ...

It supports arbitrary depths of LSTM layers in both, the encoder as well as the decoder. Similar topologies have achieved an F1 score of 95.66% in the slot filling task of the standard ATIS benchmark.

The encoder processes the input sequence, while the decoder generates the output sequence. Multiple layers of self-attention and feed-forward neural networks make up the transformer's architecture ...