本文将系统解析 Transformer 的四大主流结构（Encoder-only、Decoder-only、Encoder-Decoder、Prefix-Decoder），它们的代表模型、适用任务，以及为何 Decoder-only 能 ...

In recent years, with the rapid development of large model technology, the Transformer architecture has gained widespread attention as its core cornerstone. This article will delve into the principles ...

Seq2Seq is essentially an abstract deion of a class of problems, rather than a specific model architecture, just as the ...

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.

An Encoder-decoder architecture in machine learning efficiently translates one sequence data form to another.

Discover the key differences between Moshi and Whisper speech-to-text models. Speed, accuracy, and use cases explained for your next project.

The encoder–decoder approach was significantly faster than LLMs such as Microsoft’s Phi-3.5, which is a decoder-only model.

The key to addressing these challenges lies in separating the encoder and decoder components of multimodal machine learning models.